• So, there’s this thing about how Discord was ported to Windows 95 and NT 3.1. Honestly, it’s kind of interesting, but also a bit dull. Like, who even thinks about running Discord on those old systems? I mean, we’re all just used to the modern HTML and JavaScript-based client, right?

    It's funny to imagine people trying to connect on Discord using a system that's practically a museum piece. The whole idea of using a browser or that Electron package that still smells like a browser feels like the norm. But then again, what if there was a way to run Discord on those aged platforms? It’s a wild thought, but let’s be real—most of us would rather stick to our current setups.

    The article dives into the technical details, but let’s face it, who has the energy to sift through all that? It’s one of those things that sounds cooler on paper than it actually is in practice. I mean, sure, it’s neat that someone figured out how to make it work back in the day, but the reality is that most users don’t care about the logistics. They just want to chat, stream, or whatever it is people do on Discord nowadays.

    And it’s not like anyone is lining up to use Discord on Windows 95 or NT 3.1. I can’t even imagine the lag. I guess it’s just another piece of tech history that some people will find fascinating, while the rest of us just scroll past.

    So, yeah, that’s pretty much it. Discord on ancient systems is a thing. It happened. People did it. But let’s not pretend that it’s something we’re all eager to dive into. Honestly, I’d rather just scroll through memes or something.

    #Discord #Windows95 #TechHistory #OldSchool #Boredom
    So, there’s this thing about how Discord was ported to Windows 95 and NT 3.1. Honestly, it’s kind of interesting, but also a bit dull. Like, who even thinks about running Discord on those old systems? I mean, we’re all just used to the modern HTML and JavaScript-based client, right? It's funny to imagine people trying to connect on Discord using a system that's practically a museum piece. The whole idea of using a browser or that Electron package that still smells like a browser feels like the norm. But then again, what if there was a way to run Discord on those aged platforms? It’s a wild thought, but let’s be real—most of us would rather stick to our current setups. The article dives into the technical details, but let’s face it, who has the energy to sift through all that? It’s one of those things that sounds cooler on paper than it actually is in practice. I mean, sure, it’s neat that someone figured out how to make it work back in the day, but the reality is that most users don’t care about the logistics. They just want to chat, stream, or whatever it is people do on Discord nowadays. And it’s not like anyone is lining up to use Discord on Windows 95 or NT 3.1. I can’t even imagine the lag. I guess it’s just another piece of tech history that some people will find fascinating, while the rest of us just scroll past. So, yeah, that’s pretty much it. Discord on ancient systems is a thing. It happened. People did it. But let’s not pretend that it’s something we’re all eager to dive into. Honestly, I’d rather just scroll through memes or something. #Discord #Windows95 #TechHistory #OldSchool #Boredom
    How Discord Was Ported to Windows 95 and NT 3.1
    On the desktop, most people use the official HTML and JavaScript-based client for Discord in either a browser or a still-smells-like-a-browser Electron package. Yet what if there was a way …read more
    Like
    Love
    Wow
    Sad
    Angry
    602
    1 Σχόλια 0 Μοιράστηκε
  • Publishing your first manga might sound exciting, but honestly, it’s just a lot of work. It’s one of those things that you think will be fun, but then you realize it’s just a long journey filled with endless sketches and revisions. Six top manga artists talk about their experiences, but let’s be real, it’s not all that thrilling.

    First off, you have to come up with a story. Sounds easy, right? But then you sit there staring at a blank page, and the ideas just don’t come. You read what other artists say about their success, and it makes you feel like you should have everything figured out. They talk about characters and plots like it’s the easiest thing in the world. But between you and me, it’s exhausting.

    Then comes the drawing part. Sure, you might enjoy sketching sometimes, but doing it for hours every day? That’s where the fun starts to fade. You’ll probably go through phases where you hate your own art. It’s a cycle of drawing, erasing, and feeling disappointed. It’s not a glamorous process; it’s just a grind.

    After you’ve finally got something that resembles a story and some pages that are somewhat decent, you have to think about publishing. This is where the anxiety kicks in. Do you self-publish? Try to find a publisher? Each option has its own set of problems. You read advice from those six artists, and they all sound like they’ve got it figured out. But honestly, who has the energy to deal with all those logistics?

    Marketing is another thing. They say you need to promote yourself, build a following, and all that jazz. But scrolling through social media to post about your manga feels more like a chore than a fun activity. You might think you’ll enjoy it, but it’s just more work piled on top of everything else.

    In the end, the best advice might be to just get through it and hope for the best. You’ll survive the experience, maybe even learn something, but it’s not going to be a walk in the park. If you’re looking for a carefree journey, publishing your first manga probably isn’t it.

    So, yeah. That’s the reality. It’s not as glamorous as it sounds. You just do it, and hope that someday it might feel rewarding. But until then, it’s just a lot of waiting and wondering. Good luck, I guess.

    #Manga #Publishing #MangaArtists #Comics #ArtProcess
    Publishing your first manga might sound exciting, but honestly, it’s just a lot of work. It’s one of those things that you think will be fun, but then you realize it’s just a long journey filled with endless sketches and revisions. Six top manga artists talk about their experiences, but let’s be real, it’s not all that thrilling. First off, you have to come up with a story. Sounds easy, right? But then you sit there staring at a blank page, and the ideas just don’t come. You read what other artists say about their success, and it makes you feel like you should have everything figured out. They talk about characters and plots like it’s the easiest thing in the world. But between you and me, it’s exhausting. Then comes the drawing part. Sure, you might enjoy sketching sometimes, but doing it for hours every day? That’s where the fun starts to fade. You’ll probably go through phases where you hate your own art. It’s a cycle of drawing, erasing, and feeling disappointed. It’s not a glamorous process; it’s just a grind. After you’ve finally got something that resembles a story and some pages that are somewhat decent, you have to think about publishing. This is where the anxiety kicks in. Do you self-publish? Try to find a publisher? Each option has its own set of problems. You read advice from those six artists, and they all sound like they’ve got it figured out. But honestly, who has the energy to deal with all those logistics? Marketing is another thing. They say you need to promote yourself, build a following, and all that jazz. But scrolling through social media to post about your manga feels more like a chore than a fun activity. You might think you’ll enjoy it, but it’s just more work piled on top of everything else. In the end, the best advice might be to just get through it and hope for the best. You’ll survive the experience, maybe even learn something, but it’s not going to be a walk in the park. If you’re looking for a carefree journey, publishing your first manga probably isn’t it. So, yeah. That’s the reality. It’s not as glamorous as it sounds. You just do it, and hope that someday it might feel rewarding. But until then, it’s just a lot of waiting and wondering. Good luck, I guess. #Manga #Publishing #MangaArtists #Comics #ArtProcess
    How to publish your first manga (and survive the experience)
    Six top manga artists reveal the secrets behind their success
    Like
    Love
    Wow
    Angry
    Sad
    451
    1 Σχόλια 0 Μοιράστηκε
  • Over 8M patient records leaked in healthcare data breach

    Published
    June 15, 2025 10:00am EDT close IPhone users instructed to take immediate action to avoid data breach: 'Urgent threat' Kurt 'The CyberGuy' Knutsson discusses Elon Musk's possible priorities as he exits his role with the White House and explains the urgent warning for iPhone users to update devices after a 'massive security gap.' NEWYou can now listen to Fox News articles!
    In the past decade, healthcare data has become one of the most sought-after targets in cybercrime. From insurers to clinics, every player in the ecosystem handles some form of sensitive information. However, breaches do not always originate from hospitals or health apps. Increasingly, patient data is managed by third-party vendors offering digital services such as scheduling, billing and marketing. One such breach at a digital marketing agency serving dental practices recently exposed approximately 2.7 million patient profiles and more than 8.8 million appointment records.Sign up for my FREE CyberGuy ReportGet my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox. Plus, you’ll get instant access to my Ultimate Scam Survival Guide — free when you join. Illustration of a hacker at work  Massive healthcare data leak exposes millions: What you need to knowCybernews researchers have discovered a misconfigured MongoDB database exposing 2.7 million patient profiles and 8.8 million appointment records. The database was publicly accessible online, unprotected by passwords or authentication protocols. Anyone with basic knowledge of database scanning tools could have accessed it.The exposed data included names, birthdates, addresses, emails, phone numbers, gender, chart IDs, language preferences and billing classifications. Appointment records also contained metadata such as timestamps and institutional identifiers.MASSIVE DATA BREACH EXPOSES 184 MILLION PASSWORDS AND LOGINSClues within the data structure point toward Gargle, a Utah-based company that builds websites and offers marketing tools for dental practices. While not a confirmed source, several internal references and system details suggest a strong connection. Gargle provides appointment scheduling, form submission and patient communication services. These functions require access to patient information, making the firm a likely link in the exposure.After the issue was reported, the database was secured. The duration of the exposure remains unknown, and there is no public evidence indicating whether the data was downloaded by malicious actors before being locked down.We reached out to Gargle for a comment but did not hear back before our deadline. A healthcare professional viewing heath data     How healthcare data breaches lead to identity theft and insurance fraudThe exposed data presents a broad risk profile. On its own, a phone number or billing record might seem limited in scope. Combined, however, the dataset forms a complete profile that could be exploited for identity theft, insurance fraud and targeted phishing campaigns.Medical identity theft allows attackers to impersonate patients and access services under a false identity. Victims often remain unaware until significant damage is done, ranging from incorrect medical records to unpaid bills in their names. The leak also opens the door to insurance fraud, with actors using institutional references and chart data to submit false claims.This type of breach raises questions about compliance with the Health Insurance Portability and Accountability Act, which mandates strong security protections for entities handling patient data. Although Gargle is not a healthcare provider, its access to patient-facing infrastructure could place it under the scope of that regulation as a business associate. A healthcare professional working on a laptop  5 ways you can stay safe from healthcare data breachesIf your information was part of the healthcare breach or any similar one, it’s worth taking a few steps to protect yourself.1. Consider identity theft protection services: Since the healthcare data breach exposed personal and financial information, it’s crucial to stay proactive against identity theft. Identity theft protection services offer continuous monitoring of your credit reports, Social Security number and even the dark web to detect if your information is being misused. These services send you real-time alerts about suspicious activity, such as new credit inquiries or attempts to open accounts in your name, helping you act quickly before serious damage occurs. Beyond monitoring, many identity theft protection companies provide dedicated recovery specialists who assist you in resolving fraud issues, disputing unauthorized charges and restoring your identity if it’s compromised. See my tips and best picks on how to protect yourself from identity theft.2. Use personal data removal services: The healthcare data breach leaks loads of information about you, and all this could end up in the public domain, which essentially gives anyone an opportunity to scam you.  One proactive step is to consider personal data removal services, which specialize in continuously monitoring and removing your information from various online databases and websites. While no service promises to remove all your data from the internet, having a removal service is great if you want to constantly monitor and automate the process of removing your information from hundreds of sites continuously over a longer period of time. Check out my top picks for data removal services here. GET FOX BUSINESS ON THE GO BY CLICKING HEREGet a free scan to find out if your personal information is already out on the web3. Have strong antivirus software: Hackers have people’s email addresses and full names, which makes it easy for them to send you a phishing link that installs malware and steals all your data. These messages are socially engineered to catch them, and catching them is nearly impossible if you’re not careful. However, you’re not without defenses.The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have strong antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe. Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android and iOS devices.4. Enable two-factor authentication: While passwords weren’t part of the data breach, you still need to enable two-factor authentication. It gives you an extra layer of security on all your important accounts, including email, banking and social media. 2FA requires you to provide a second piece of information, such as a code sent to your phone, in addition to your password when logging in. This makes it significantly harder for hackers to access your accounts, even if they have your password. Enabling 2FA can greatly reduce the risk of unauthorized access and protect your sensitive data.5. Be wary of mailbox communications: Bad actors may also try to scam you through snail mail. The data leak gives them access to your address. They may impersonate people or brands you know and use themes that require urgent attention, such as missed deliveries, account suspensions and security alerts. Kurt’s key takeawayIf nothing else, this latest leak shows just how poorly patient data is being handled today. More and more, non-medical vendors are getting access to sensitive information without facing the same rules or oversight as hospitals and clinics. These third-party services are now a regular part of how patients book appointments, pay bills or fill out forms. But when something goes wrong, the fallout is just as serious. Even though the database was taken offline, the bigger problem hasn't gone away. Your data is only as safe as the least careful company that gets access to it.CLICK HERE TO GET THE FOX NEWS APPDo you think healthcare companies are investing enough in their cybersecurity infrastructure? Let us know by writing us at Cyberguy.com/ContactFor more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/NewsletterAsk Kurt a question or let us know what stories you'd like us to coverFollow Kurt on his social channelsAnswers to the most asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com.  All rights reserved.   Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com.
    #over #patient #records #leaked #healthcare
    Over 8M patient records leaked in healthcare data breach
    Published June 15, 2025 10:00am EDT close IPhone users instructed to take immediate action to avoid data breach: 'Urgent threat' Kurt 'The CyberGuy' Knutsson discusses Elon Musk's possible priorities as he exits his role with the White House and explains the urgent warning for iPhone users to update devices after a 'massive security gap.' NEWYou can now listen to Fox News articles! In the past decade, healthcare data has become one of the most sought-after targets in cybercrime. From insurers to clinics, every player in the ecosystem handles some form of sensitive information. However, breaches do not always originate from hospitals or health apps. Increasingly, patient data is managed by third-party vendors offering digital services such as scheduling, billing and marketing. One such breach at a digital marketing agency serving dental practices recently exposed approximately 2.7 million patient profiles and more than 8.8 million appointment records.Sign up for my FREE CyberGuy ReportGet my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox. Plus, you’ll get instant access to my Ultimate Scam Survival Guide — free when you join. Illustration of a hacker at work  Massive healthcare data leak exposes millions: What you need to knowCybernews researchers have discovered a misconfigured MongoDB database exposing 2.7 million patient profiles and 8.8 million appointment records. The database was publicly accessible online, unprotected by passwords or authentication protocols. Anyone with basic knowledge of database scanning tools could have accessed it.The exposed data included names, birthdates, addresses, emails, phone numbers, gender, chart IDs, language preferences and billing classifications. Appointment records also contained metadata such as timestamps and institutional identifiers.MASSIVE DATA BREACH EXPOSES 184 MILLION PASSWORDS AND LOGINSClues within the data structure point toward Gargle, a Utah-based company that builds websites and offers marketing tools for dental practices. While not a confirmed source, several internal references and system details suggest a strong connection. Gargle provides appointment scheduling, form submission and patient communication services. These functions require access to patient information, making the firm a likely link in the exposure.After the issue was reported, the database was secured. The duration of the exposure remains unknown, and there is no public evidence indicating whether the data was downloaded by malicious actors before being locked down.We reached out to Gargle for a comment but did not hear back before our deadline. A healthcare professional viewing heath data     How healthcare data breaches lead to identity theft and insurance fraudThe exposed data presents a broad risk profile. On its own, a phone number or billing record might seem limited in scope. Combined, however, the dataset forms a complete profile that could be exploited for identity theft, insurance fraud and targeted phishing campaigns.Medical identity theft allows attackers to impersonate patients and access services under a false identity. Victims often remain unaware until significant damage is done, ranging from incorrect medical records to unpaid bills in their names. The leak also opens the door to insurance fraud, with actors using institutional references and chart data to submit false claims.This type of breach raises questions about compliance with the Health Insurance Portability and Accountability Act, which mandates strong security protections for entities handling patient data. Although Gargle is not a healthcare provider, its access to patient-facing infrastructure could place it under the scope of that regulation as a business associate. A healthcare professional working on a laptop  5 ways you can stay safe from healthcare data breachesIf your information was part of the healthcare breach or any similar one, it’s worth taking a few steps to protect yourself.1. Consider identity theft protection services: Since the healthcare data breach exposed personal and financial information, it’s crucial to stay proactive against identity theft. Identity theft protection services offer continuous monitoring of your credit reports, Social Security number and even the dark web to detect if your information is being misused. These services send you real-time alerts about suspicious activity, such as new credit inquiries or attempts to open accounts in your name, helping you act quickly before serious damage occurs. Beyond monitoring, many identity theft protection companies provide dedicated recovery specialists who assist you in resolving fraud issues, disputing unauthorized charges and restoring your identity if it’s compromised. See my tips and best picks on how to protect yourself from identity theft.2. Use personal data removal services: The healthcare data breach leaks loads of information about you, and all this could end up in the public domain, which essentially gives anyone an opportunity to scam you.  One proactive step is to consider personal data removal services, which specialize in continuously monitoring and removing your information from various online databases and websites. While no service promises to remove all your data from the internet, having a removal service is great if you want to constantly monitor and automate the process of removing your information from hundreds of sites continuously over a longer period of time. Check out my top picks for data removal services here. GET FOX BUSINESS ON THE GO BY CLICKING HEREGet a free scan to find out if your personal information is already out on the web3. Have strong antivirus software: Hackers have people’s email addresses and full names, which makes it easy for them to send you a phishing link that installs malware and steals all your data. These messages are socially engineered to catch them, and catching them is nearly impossible if you’re not careful. However, you’re not without defenses.The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have strong antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe. Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android and iOS devices.4. Enable two-factor authentication: While passwords weren’t part of the data breach, you still need to enable two-factor authentication. It gives you an extra layer of security on all your important accounts, including email, banking and social media. 2FA requires you to provide a second piece of information, such as a code sent to your phone, in addition to your password when logging in. This makes it significantly harder for hackers to access your accounts, even if they have your password. Enabling 2FA can greatly reduce the risk of unauthorized access and protect your sensitive data.5. Be wary of mailbox communications: Bad actors may also try to scam you through snail mail. The data leak gives them access to your address. They may impersonate people or brands you know and use themes that require urgent attention, such as missed deliveries, account suspensions and security alerts. Kurt’s key takeawayIf nothing else, this latest leak shows just how poorly patient data is being handled today. More and more, non-medical vendors are getting access to sensitive information without facing the same rules or oversight as hospitals and clinics. These third-party services are now a regular part of how patients book appointments, pay bills or fill out forms. But when something goes wrong, the fallout is just as serious. Even though the database was taken offline, the bigger problem hasn't gone away. Your data is only as safe as the least careful company that gets access to it.CLICK HERE TO GET THE FOX NEWS APPDo you think healthcare companies are investing enough in their cybersecurity infrastructure? Let us know by writing us at Cyberguy.com/ContactFor more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/NewsletterAsk Kurt a question or let us know what stories you'd like us to coverFollow Kurt on his social channelsAnswers to the most asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com.  All rights reserved.   Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com. #over #patient #records #leaked #healthcare
    WWW.FOXNEWS.COM
    Over 8M patient records leaked in healthcare data breach
    Published June 15, 2025 10:00am EDT close IPhone users instructed to take immediate action to avoid data breach: 'Urgent threat' Kurt 'The CyberGuy' Knutsson discusses Elon Musk's possible priorities as he exits his role with the White House and explains the urgent warning for iPhone users to update devices after a 'massive security gap.' NEWYou can now listen to Fox News articles! In the past decade, healthcare data has become one of the most sought-after targets in cybercrime. From insurers to clinics, every player in the ecosystem handles some form of sensitive information. However, breaches do not always originate from hospitals or health apps. Increasingly, patient data is managed by third-party vendors offering digital services such as scheduling, billing and marketing. One such breach at a digital marketing agency serving dental practices recently exposed approximately 2.7 million patient profiles and more than 8.8 million appointment records.Sign up for my FREE CyberGuy ReportGet my best tech tips, urgent security alerts, and exclusive deals delivered straight to your inbox. Plus, you’ll get instant access to my Ultimate Scam Survival Guide — free when you join. Illustration of a hacker at work   (Kurt "CyberGuy" Knutsson)Massive healthcare data leak exposes millions: What you need to knowCybernews researchers have discovered a misconfigured MongoDB database exposing 2.7 million patient profiles and 8.8 million appointment records. The database was publicly accessible online, unprotected by passwords or authentication protocols. Anyone with basic knowledge of database scanning tools could have accessed it.The exposed data included names, birthdates, addresses, emails, phone numbers, gender, chart IDs, language preferences and billing classifications. Appointment records also contained metadata such as timestamps and institutional identifiers.MASSIVE DATA BREACH EXPOSES 184 MILLION PASSWORDS AND LOGINSClues within the data structure point toward Gargle, a Utah-based company that builds websites and offers marketing tools for dental practices. While not a confirmed source, several internal references and system details suggest a strong connection. Gargle provides appointment scheduling, form submission and patient communication services. These functions require access to patient information, making the firm a likely link in the exposure.After the issue was reported, the database was secured. The duration of the exposure remains unknown, and there is no public evidence indicating whether the data was downloaded by malicious actors before being locked down.We reached out to Gargle for a comment but did not hear back before our deadline. A healthcare professional viewing heath data      (Kurt "CyberGuy" Knutsson)How healthcare data breaches lead to identity theft and insurance fraudThe exposed data presents a broad risk profile. On its own, a phone number or billing record might seem limited in scope. Combined, however, the dataset forms a complete profile that could be exploited for identity theft, insurance fraud and targeted phishing campaigns.Medical identity theft allows attackers to impersonate patients and access services under a false identity. Victims often remain unaware until significant damage is done, ranging from incorrect medical records to unpaid bills in their names. The leak also opens the door to insurance fraud, with actors using institutional references and chart data to submit false claims.This type of breach raises questions about compliance with the Health Insurance Portability and Accountability Act, which mandates strong security protections for entities handling patient data. Although Gargle is not a healthcare provider, its access to patient-facing infrastructure could place it under the scope of that regulation as a business associate. A healthcare professional working on a laptop   (Kurt "CyberGuy" Knutsson)5 ways you can stay safe from healthcare data breachesIf your information was part of the healthcare breach or any similar one, it’s worth taking a few steps to protect yourself.1. Consider identity theft protection services: Since the healthcare data breach exposed personal and financial information, it’s crucial to stay proactive against identity theft. Identity theft protection services offer continuous monitoring of your credit reports, Social Security number and even the dark web to detect if your information is being misused. These services send you real-time alerts about suspicious activity, such as new credit inquiries or attempts to open accounts in your name, helping you act quickly before serious damage occurs. Beyond monitoring, many identity theft protection companies provide dedicated recovery specialists who assist you in resolving fraud issues, disputing unauthorized charges and restoring your identity if it’s compromised. See my tips and best picks on how to protect yourself from identity theft.2. Use personal data removal services: The healthcare data breach leaks loads of information about you, and all this could end up in the public domain, which essentially gives anyone an opportunity to scam you.  One proactive step is to consider personal data removal services, which specialize in continuously monitoring and removing your information from various online databases and websites. While no service promises to remove all your data from the internet, having a removal service is great if you want to constantly monitor and automate the process of removing your information from hundreds of sites continuously over a longer period of time. Check out my top picks for data removal services here. GET FOX BUSINESS ON THE GO BY CLICKING HEREGet a free scan to find out if your personal information is already out on the web3. Have strong antivirus software: Hackers have people’s email addresses and full names, which makes it easy for them to send you a phishing link that installs malware and steals all your data. These messages are socially engineered to catch them, and catching them is nearly impossible if you’re not careful. However, you’re not without defenses.The best way to safeguard yourself from malicious links that install malware, potentially accessing your private information, is to have strong antivirus software installed on all your devices. This protection can also alert you to phishing emails and ransomware scams, keeping your personal information and digital assets safe. Get my picks for the best 2025 antivirus protection winners for your Windows, Mac, Android and iOS devices.4. Enable two-factor authentication: While passwords weren’t part of the data breach, you still need to enable two-factor authentication (2FA). It gives you an extra layer of security on all your important accounts, including email, banking and social media. 2FA requires you to provide a second piece of information, such as a code sent to your phone, in addition to your password when logging in. This makes it significantly harder for hackers to access your accounts, even if they have your password. Enabling 2FA can greatly reduce the risk of unauthorized access and protect your sensitive data.5. Be wary of mailbox communications: Bad actors may also try to scam you through snail mail. The data leak gives them access to your address. They may impersonate people or brands you know and use themes that require urgent attention, such as missed deliveries, account suspensions and security alerts. Kurt’s key takeawayIf nothing else, this latest leak shows just how poorly patient data is being handled today. More and more, non-medical vendors are getting access to sensitive information without facing the same rules or oversight as hospitals and clinics. These third-party services are now a regular part of how patients book appointments, pay bills or fill out forms. But when something goes wrong, the fallout is just as serious. Even though the database was taken offline, the bigger problem hasn't gone away. Your data is only as safe as the least careful company that gets access to it.CLICK HERE TO GET THE FOX NEWS APPDo you think healthcare companies are investing enough in their cybersecurity infrastructure? Let us know by writing us at Cyberguy.com/ContactFor more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/NewsletterAsk Kurt a question or let us know what stories you'd like us to coverFollow Kurt on his social channelsAnswers to the most asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com.  All rights reserved.   Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com.
    Like
    Love
    Wow
    Sad
    Angry
    507
    0 Σχόλια 0 Μοιράστηκε
  • New Zealand’s Email Security Requirements for Government Organizations: What You Need to Know

    The Secure Government EmailCommon Implementation Framework
    New Zealand’s government is introducing a comprehensive email security framework designed to protect official communications from phishing and domain spoofing. This new framework, which will be mandatory for all government agencies by October 2025, establishes clear technical standards to enhance email security and retire the outdated SEEMail service. 
    Key Takeaways

    All NZ government agencies must comply with new email security requirements by October 2025.
    The new framework strengthens trust and security in government communications by preventing spoofing and phishing.
    The framework mandates TLS 1.2+, SPF, DKIM, DMARC with p=reject, MTA-STS, and DLP controls.
    EasyDMARC simplifies compliance with our guided setup, monitoring, and automated reporting.

    Start a Free Trial

    What is the Secure Government Email Common Implementation Framework?
    The Secure Government EmailCommon Implementation Framework is a new government-led initiative in New Zealand designed to standardize email security across all government agencies. Its main goal is to secure external email communication, reduce domain spoofing in phishing attacks, and replace the legacy SEEMail service.
    Why is New Zealand Implementing New Government Email Security Standards?
    The framework was developed by New Zealand’s Department of Internal Affairsas part of its role in managing ICT Common Capabilities. It leverages modern email security controls via the Domain Name Systemto enable the retirement of the legacy SEEMail service and provide:

    Encryption for transmission security
    Digital signing for message integrity
    Basic non-repudiationDomain spoofing protection

    These improvements apply to all emails, not just those routed through SEEMail, offering broader protection across agency communications.
    What Email Security Technologies Are Required by the New NZ SGE Framework?
    The SGE Framework outlines the following key technologies that agencies must implement:

    TLS 1.2 or higher with implicit TLS enforced
    TLS-RPTSPFDKIMDMARCwith reporting
    MTA-STSData Loss Prevention controls

    These technologies work together to ensure encrypted email transmission, validate sender identity, prevent unauthorized use of domains, and reduce the risk of sensitive data leaks.

    Get in touch

    When Do NZ Government Agencies Need to Comply with this Framework?
    All New Zealand government agencies are expected to fully implement the Secure Government EmailCommon Implementation Framework by October 2025. Agencies should begin their planning and deployment now to ensure full compliance by the deadline.
    The All of Government Secure Email Common Implementation Framework v1.0
    What are the Mandated Requirements for Domains?
    Below are the exact requirements for all email-enabled domains under the new framework.
    ControlExact RequirementTLSMinimum TLS 1.2. TLS 1.1, 1.0, SSL, or clear-text not permitted.TLS-RPTAll email-sending domains must have TLS reporting enabled.SPFMust exist and end with -all.DKIMAll outbound email from every sending service must be DKIM-signed at the final hop.DMARCPolicy of p=reject on all email-enabled domains. adkim=s is recommended when not bulk-sending.MTA-STSEnabled and set to enforce.Implicit TLSMust be configured and enforced for every connection.Data Loss PreventionEnforce in line with the New Zealand Information Security Manualand Protective Security Requirements.
    Compliance Monitoring and Reporting
    The All of Government Service Deliveryteam will be monitoring compliance with the framework. Monitoring will initially cover SPF, DMARC, and MTA-STS settings and will be expanded to include DKIM. Changes to these settings will be monitored, enabling reporting on email security compliance across all government agencies. Ongoing monitoring will highlight changes to domains, ensure new domains are set up with security in place, and monitor the implementation of future email security technologies. 
    Should compliance changes occur, such as an agency’s SPF record being changed from -all to ~all, this will be captured so that the AoGSD Security Team can investigate. They will then communicate directly with the agency to determine if an issue exists or if an error has occurred, reviewing each case individually.
    Deployment Checklist for NZ Government Compliance

    Enforce TLS 1.2 minimum, implicit TLS, MTA-STS & TLS-RPT
    SPF with -all
    DKIM on all outbound email
    DMARC p=reject 
    adkim=s where suitable
    For non-email/parked domains: SPF -all, empty DKIM, DMARC reject strict
    Compliance dashboard
    Inbound DMARC evaluation enforced
    DLP aligned with NZISM

    Start a Free Trial

    How EasyDMARC Can Help Government Agencies Comply
    EasyDMARC provides a comprehensive email security solution that simplifies the deployment and ongoing management of DNS-based email security protocols like SPF, DKIM, and DMARC with reporting. Our platform offers automated checks, real-time monitoring, and a guided setup to help government organizations quickly reach compliance.
    1. TLS-RPT / MTA-STS audit
    EasyDMARC enables you to enable the Managed MTA-STS and TLS-RPT option with a single click. We provide the required DNS records and continuously monitor them for issues, delivering reports on TLS negotiation problems. This helps agencies ensure secure email transmission and quickly detect delivery or encryption failures.

    Note: In this screenshot, you can see how to deploy MTA-STS and TLS Reporting by adding just three CNAME records provided by EasyDMARC. It’s recommended to start in “testing” mode, evaluate the TLS-RPT reports, and then gradually switch your MTA-STS policy to “enforce”. The process is simple and takes just a few clicks.

    As shown above, EasyDMARC parses incoming TLS reports into a centralized dashboard, giving you clear visibility into delivery and encryption issues across all sending sources.
    2. SPF with “-all”In the EasyDARC platform, you can run the SPF Record Generator to create a compliant record. Publish your v=spf1 record with “-all” to enforce a hard fail for unauthorized senders and prevent spoofed emails from passing SPF checks. This strengthens your domain’s protection against impersonation.

    Note: It is highly recommended to start adjusting your SPF record only after you begin receiving DMARC reports and identifying your legitimate email sources. As we’ll explain in more detail below, both SPF and DKIM should be adjusted after you gain visibility through reports.
    Making changes without proper visibility can lead to false positives, misconfigurations, and potential loss of legitimate emails. That’s why the first step should always be setting DMARC to p=none, receiving reports, analyzing them, and then gradually fixing any SPF or DKIM issues.
    3. DKIM on all outbound email
    DKIM must be configured for all email sources sending emails on behalf of your domain. This is critical, as DKIM plays a bigger role than SPF when it comes to building domain reputation, surviving auto-forwarding, mailing lists, and other edge cases.
    As mentioned above, DMARC reports provide visibility into your email sources, allowing you to implement DKIM accordingly. If you’re using third-party services like Google Workspace, Microsoft 365, or Mimecast, you’ll need to retrieve the public DKIM key from your provider’s admin interface.
    EasyDMARC maintains a backend directory of over 1,400 email sources. We also give you detailed guidance on how to configure SPF and DKIM correctly for major ESPs. 
    Note: At the end of this article, you’ll find configuration links for well-known ESPs like Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid – helping you avoid common misconfigurations and get aligned with SGE requirements.
    If you’re using a dedicated MTA, DKIM must be implemented manually. EasyDMARC’s DKIM Record Generator lets you generate both public and private keys for your server. The private key is stored on your MTA, while the public key must be published in your DNS.

    4. DMARC p=reject rollout
    As mentioned in previous points, DMARC reporting is the first and most important step on your DMARC enforcement journey. Always start with a p=none policy and configure RUA reports to be sent to EasyDMARC. Use the report insights to identify and fix SPF and DKIM alignment issues, then gradually move to p=quarantine and finally p=reject once all legitimate email sources have been authenticated. 
    This phased approach ensures full protection against domain spoofing without risking legitimate email delivery.

    5. adkim Strict Alignment Check
    This strict alignment check is not always applicable, especially if you’re using third-party bulk ESPs, such as Sendgrid, that require you to set DKIM on a subdomain level. You can set adkim=s in your DMARC TXT record, or simply enable strict mode in EasyDMARC’s Managed DMARC settings. This ensures that only emails with a DKIM signature that exactly match your domain pass alignment, adding an extra layer of protection against domain spoofing. But only do this if you are NOT a bulk sender.

    6. Securing Non-Email Enabled Domains
    The purpose of deploying email security to non-email-enabled domains, or parked domains, is to prevent messages being spoofed from that domain. This requirement remains even if the root-level domain has SP=reject set within its DMARC record.
    Under this new framework, you must bulk import and mark parked domains as “Parked.” Crucially, this requires adjusting SPF settings to an empty record, setting DMARC to p=reject, and ensuring an empty DKIM record is in place: • SPF record: “v=spf1 -all”.
    • Wildcard DKIM record with empty public key.• DMARC record: “v=DMARC1;p=reject;adkim=s;aspf=s;rua=mailto:…”.
    EasyDMARC allows you to add and label parked domains for free. This is important because it helps you monitor any activity from these domains and ensure they remain protected with a strict DMARC policy of p=reject.
    7. Compliance Dashboard
    Use EasyDMARC’s Domain Scanner to assess the security posture of each domain with a clear compliance score and risk level. The dashboard highlights configuration gaps and guides remediation steps, helping government agencies stay on track toward full compliance with the SGE Framework.

    8. Inbound DMARC Evaluation Enforced
    You don’t need to apply any changes if you’re using Google Workspace, Microsoft 365, or other major mailbox providers. Most of them already enforce DMARC evaluation on incoming emails.
    However, some legacy Microsoft 365 setups may still quarantine emails that fail DMARC checks, even when the sending domain has a p=reject policy, instead of rejecting them. This behavior can be adjusted directly from your Microsoft Defender portal. about this in our step-by-step guide on how to set up SPF, DKIM, and DMARC from Microsoft Defender.
    If you’re using a third-party mail provider that doesn’t enforce having a DMARC policy for incoming emails, which is rare, you’ll need to contact their support to request a configuration change.
    9. Data Loss Prevention Aligned with NZISM
    The New Zealand Information Security Manualis the New Zealand Government’s manual on information assurance and information systems security. It includes guidance on data loss prevention, which must be followed to be aligned with the SEG.
    Need Help Setting up SPF and DKIM for your Email Provider?
    Setting up SPF and DKIM for different ESPs often requires specific configurations. Some providers require you to publish SPF and DKIM on a subdomain, while others only require DKIM, or have different formatting rules. We’ve simplified all these steps to help you avoid misconfigurations that could delay your DMARC enforcement, or worse, block legitimate emails from reaching your recipients.
    Below you’ll find comprehensive setup guides for Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid. You can also explore our full blog section that covers setup instructions for many other well-known ESPs.
    Remember, all this information is reflected in your DMARC aggregate reports. These reports give you live visibility into your outgoing email ecosystem, helping you analyze and fix any issues specific to a given provider.
    Here are our step-by-step guides for the most common platforms:

    Google Workspace

    Microsoft 365

    These guides will help ensure your DNS records are configured correctly as part of the Secure Government EmailFramework rollout.
    Meet New Government Email Security Standards With EasyDMARC
    New Zealand’s SEG Framework sets a clear path for government agencies to enhance their email security by October 2025. With EasyDMARC, you can meet these technical requirements efficiently and with confidence. From protocol setup to continuous monitoring and compliance tracking, EasyDMARC streamlines the entire process, ensuring strong protection against spoofing, phishing, and data loss while simplifying your transition from SEEMail.
    #new #zealands #email #security #requirements
    New Zealand’s Email Security Requirements for Government Organizations: What You Need to Know
    The Secure Government EmailCommon Implementation Framework New Zealand’s government is introducing a comprehensive email security framework designed to protect official communications from phishing and domain spoofing. This new framework, which will be mandatory for all government agencies by October 2025, establishes clear technical standards to enhance email security and retire the outdated SEEMail service.  Key Takeaways All NZ government agencies must comply with new email security requirements by October 2025. The new framework strengthens trust and security in government communications by preventing spoofing and phishing. The framework mandates TLS 1.2+, SPF, DKIM, DMARC with p=reject, MTA-STS, and DLP controls. EasyDMARC simplifies compliance with our guided setup, monitoring, and automated reporting. Start a Free Trial What is the Secure Government Email Common Implementation Framework? The Secure Government EmailCommon Implementation Framework is a new government-led initiative in New Zealand designed to standardize email security across all government agencies. Its main goal is to secure external email communication, reduce domain spoofing in phishing attacks, and replace the legacy SEEMail service. Why is New Zealand Implementing New Government Email Security Standards? The framework was developed by New Zealand’s Department of Internal Affairsas part of its role in managing ICT Common Capabilities. It leverages modern email security controls via the Domain Name Systemto enable the retirement of the legacy SEEMail service and provide: Encryption for transmission security Digital signing for message integrity Basic non-repudiationDomain spoofing protection These improvements apply to all emails, not just those routed through SEEMail, offering broader protection across agency communications. What Email Security Technologies Are Required by the New NZ SGE Framework? The SGE Framework outlines the following key technologies that agencies must implement: TLS 1.2 or higher with implicit TLS enforced TLS-RPTSPFDKIMDMARCwith reporting MTA-STSData Loss Prevention controls These technologies work together to ensure encrypted email transmission, validate sender identity, prevent unauthorized use of domains, and reduce the risk of sensitive data leaks. Get in touch When Do NZ Government Agencies Need to Comply with this Framework? All New Zealand government agencies are expected to fully implement the Secure Government EmailCommon Implementation Framework by October 2025. Agencies should begin their planning and deployment now to ensure full compliance by the deadline. The All of Government Secure Email Common Implementation Framework v1.0 What are the Mandated Requirements for Domains? Below are the exact requirements for all email-enabled domains under the new framework. ControlExact RequirementTLSMinimum TLS 1.2. TLS 1.1, 1.0, SSL, or clear-text not permitted.TLS-RPTAll email-sending domains must have TLS reporting enabled.SPFMust exist and end with -all.DKIMAll outbound email from every sending service must be DKIM-signed at the final hop.DMARCPolicy of p=reject on all email-enabled domains. adkim=s is recommended when not bulk-sending.MTA-STSEnabled and set to enforce.Implicit TLSMust be configured and enforced for every connection.Data Loss PreventionEnforce in line with the New Zealand Information Security Manualand Protective Security Requirements. Compliance Monitoring and Reporting The All of Government Service Deliveryteam will be monitoring compliance with the framework. Monitoring will initially cover SPF, DMARC, and MTA-STS settings and will be expanded to include DKIM. Changes to these settings will be monitored, enabling reporting on email security compliance across all government agencies. Ongoing monitoring will highlight changes to domains, ensure new domains are set up with security in place, and monitor the implementation of future email security technologies.  Should compliance changes occur, such as an agency’s SPF record being changed from -all to ~all, this will be captured so that the AoGSD Security Team can investigate. They will then communicate directly with the agency to determine if an issue exists or if an error has occurred, reviewing each case individually. Deployment Checklist for NZ Government Compliance Enforce TLS 1.2 minimum, implicit TLS, MTA-STS & TLS-RPT SPF with -all DKIM on all outbound email DMARC p=reject  adkim=s where suitable For non-email/parked domains: SPF -all, empty DKIM, DMARC reject strict Compliance dashboard Inbound DMARC evaluation enforced DLP aligned with NZISM Start a Free Trial How EasyDMARC Can Help Government Agencies Comply EasyDMARC provides a comprehensive email security solution that simplifies the deployment and ongoing management of DNS-based email security protocols like SPF, DKIM, and DMARC with reporting. Our platform offers automated checks, real-time monitoring, and a guided setup to help government organizations quickly reach compliance. 1. TLS-RPT / MTA-STS audit EasyDMARC enables you to enable the Managed MTA-STS and TLS-RPT option with a single click. We provide the required DNS records and continuously monitor them for issues, delivering reports on TLS negotiation problems. This helps agencies ensure secure email transmission and quickly detect delivery or encryption failures. Note: In this screenshot, you can see how to deploy MTA-STS and TLS Reporting by adding just three CNAME records provided by EasyDMARC. It’s recommended to start in “testing” mode, evaluate the TLS-RPT reports, and then gradually switch your MTA-STS policy to “enforce”. The process is simple and takes just a few clicks. As shown above, EasyDMARC parses incoming TLS reports into a centralized dashboard, giving you clear visibility into delivery and encryption issues across all sending sources. 2. SPF with “-all”In the EasyDARC platform, you can run the SPF Record Generator to create a compliant record. Publish your v=spf1 record with “-all” to enforce a hard fail for unauthorized senders and prevent spoofed emails from passing SPF checks. This strengthens your domain’s protection against impersonation. Note: It is highly recommended to start adjusting your SPF record only after you begin receiving DMARC reports and identifying your legitimate email sources. As we’ll explain in more detail below, both SPF and DKIM should be adjusted after you gain visibility through reports. Making changes without proper visibility can lead to false positives, misconfigurations, and potential loss of legitimate emails. That’s why the first step should always be setting DMARC to p=none, receiving reports, analyzing them, and then gradually fixing any SPF or DKIM issues. 3. DKIM on all outbound email DKIM must be configured for all email sources sending emails on behalf of your domain. This is critical, as DKIM plays a bigger role than SPF when it comes to building domain reputation, surviving auto-forwarding, mailing lists, and other edge cases. As mentioned above, DMARC reports provide visibility into your email sources, allowing you to implement DKIM accordingly. If you’re using third-party services like Google Workspace, Microsoft 365, or Mimecast, you’ll need to retrieve the public DKIM key from your provider’s admin interface. EasyDMARC maintains a backend directory of over 1,400 email sources. We also give you detailed guidance on how to configure SPF and DKIM correctly for major ESPs.  Note: At the end of this article, you’ll find configuration links for well-known ESPs like Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid – helping you avoid common misconfigurations and get aligned with SGE requirements. If you’re using a dedicated MTA, DKIM must be implemented manually. EasyDMARC’s DKIM Record Generator lets you generate both public and private keys for your server. The private key is stored on your MTA, while the public key must be published in your DNS. 4. DMARC p=reject rollout As mentioned in previous points, DMARC reporting is the first and most important step on your DMARC enforcement journey. Always start with a p=none policy and configure RUA reports to be sent to EasyDMARC. Use the report insights to identify and fix SPF and DKIM alignment issues, then gradually move to p=quarantine and finally p=reject once all legitimate email sources have been authenticated.  This phased approach ensures full protection against domain spoofing without risking legitimate email delivery. 5. adkim Strict Alignment Check This strict alignment check is not always applicable, especially if you’re using third-party bulk ESPs, such as Sendgrid, that require you to set DKIM on a subdomain level. You can set adkim=s in your DMARC TXT record, or simply enable strict mode in EasyDMARC’s Managed DMARC settings. This ensures that only emails with a DKIM signature that exactly match your domain pass alignment, adding an extra layer of protection against domain spoofing. But only do this if you are NOT a bulk sender. 6. Securing Non-Email Enabled Domains The purpose of deploying email security to non-email-enabled domains, or parked domains, is to prevent messages being spoofed from that domain. This requirement remains even if the root-level domain has SP=reject set within its DMARC record. Under this new framework, you must bulk import and mark parked domains as “Parked.” Crucially, this requires adjusting SPF settings to an empty record, setting DMARC to p=reject, and ensuring an empty DKIM record is in place: • SPF record: “v=spf1 -all”. • Wildcard DKIM record with empty public key.• DMARC record: “v=DMARC1;p=reject;adkim=s;aspf=s;rua=mailto:…”. EasyDMARC allows you to add and label parked domains for free. This is important because it helps you monitor any activity from these domains and ensure they remain protected with a strict DMARC policy of p=reject. 7. Compliance Dashboard Use EasyDMARC’s Domain Scanner to assess the security posture of each domain with a clear compliance score and risk level. The dashboard highlights configuration gaps and guides remediation steps, helping government agencies stay on track toward full compliance with the SGE Framework. 8. Inbound DMARC Evaluation Enforced You don’t need to apply any changes if you’re using Google Workspace, Microsoft 365, or other major mailbox providers. Most of them already enforce DMARC evaluation on incoming emails. However, some legacy Microsoft 365 setups may still quarantine emails that fail DMARC checks, even when the sending domain has a p=reject policy, instead of rejecting them. This behavior can be adjusted directly from your Microsoft Defender portal. about this in our step-by-step guide on how to set up SPF, DKIM, and DMARC from Microsoft Defender. If you’re using a third-party mail provider that doesn’t enforce having a DMARC policy for incoming emails, which is rare, you’ll need to contact their support to request a configuration change. 9. Data Loss Prevention Aligned with NZISM The New Zealand Information Security Manualis the New Zealand Government’s manual on information assurance and information systems security. It includes guidance on data loss prevention, which must be followed to be aligned with the SEG. Need Help Setting up SPF and DKIM for your Email Provider? Setting up SPF and DKIM for different ESPs often requires specific configurations. Some providers require you to publish SPF and DKIM on a subdomain, while others only require DKIM, or have different formatting rules. We’ve simplified all these steps to help you avoid misconfigurations that could delay your DMARC enforcement, or worse, block legitimate emails from reaching your recipients. Below you’ll find comprehensive setup guides for Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid. You can also explore our full blog section that covers setup instructions for many other well-known ESPs. Remember, all this information is reflected in your DMARC aggregate reports. These reports give you live visibility into your outgoing email ecosystem, helping you analyze and fix any issues specific to a given provider. Here are our step-by-step guides for the most common platforms: Google Workspace Microsoft 365 These guides will help ensure your DNS records are configured correctly as part of the Secure Government EmailFramework rollout. Meet New Government Email Security Standards With EasyDMARC New Zealand’s SEG Framework sets a clear path for government agencies to enhance their email security by October 2025. With EasyDMARC, you can meet these technical requirements efficiently and with confidence. From protocol setup to continuous monitoring and compliance tracking, EasyDMARC streamlines the entire process, ensuring strong protection against spoofing, phishing, and data loss while simplifying your transition from SEEMail. #new #zealands #email #security #requirements
    EASYDMARC.COM
    New Zealand’s Email Security Requirements for Government Organizations: What You Need to Know
    The Secure Government Email (SGE) Common Implementation Framework New Zealand’s government is introducing a comprehensive email security framework designed to protect official communications from phishing and domain spoofing. This new framework, which will be mandatory for all government agencies by October 2025, establishes clear technical standards to enhance email security and retire the outdated SEEMail service.  Key Takeaways All NZ government agencies must comply with new email security requirements by October 2025. The new framework strengthens trust and security in government communications by preventing spoofing and phishing. The framework mandates TLS 1.2+, SPF, DKIM, DMARC with p=reject, MTA-STS, and DLP controls. EasyDMARC simplifies compliance with our guided setup, monitoring, and automated reporting. Start a Free Trial What is the Secure Government Email Common Implementation Framework? The Secure Government Email (SGE) Common Implementation Framework is a new government-led initiative in New Zealand designed to standardize email security across all government agencies. Its main goal is to secure external email communication, reduce domain spoofing in phishing attacks, and replace the legacy SEEMail service. Why is New Zealand Implementing New Government Email Security Standards? The framework was developed by New Zealand’s Department of Internal Affairs (DIA) as part of its role in managing ICT Common Capabilities. It leverages modern email security controls via the Domain Name System (DNS) to enable the retirement of the legacy SEEMail service and provide: Encryption for transmission security Digital signing for message integrity Basic non-repudiation (by allowing only authorized senders) Domain spoofing protection These improvements apply to all emails, not just those routed through SEEMail, offering broader protection across agency communications. What Email Security Technologies Are Required by the New NZ SGE Framework? The SGE Framework outlines the following key technologies that agencies must implement: TLS 1.2 or higher with implicit TLS enforced TLS-RPT (TLS Reporting) SPF (Sender Policy Framework) DKIM (DomainKeys Identified Mail) DMARC (Domain-based Message Authentication, Reporting, and Conformance) with reporting MTA-STS (Mail Transfer Agent Strict Transport Security) Data Loss Prevention controls These technologies work together to ensure encrypted email transmission, validate sender identity, prevent unauthorized use of domains, and reduce the risk of sensitive data leaks. Get in touch When Do NZ Government Agencies Need to Comply with this Framework? All New Zealand government agencies are expected to fully implement the Secure Government Email (SGE) Common Implementation Framework by October 2025. Agencies should begin their planning and deployment now to ensure full compliance by the deadline. The All of Government Secure Email Common Implementation Framework v1.0 What are the Mandated Requirements for Domains? Below are the exact requirements for all email-enabled domains under the new framework. ControlExact RequirementTLSMinimum TLS 1.2. TLS 1.1, 1.0, SSL, or clear-text not permitted.TLS-RPTAll email-sending domains must have TLS reporting enabled.SPFMust exist and end with -all.DKIMAll outbound email from every sending service must be DKIM-signed at the final hop.DMARCPolicy of p=reject on all email-enabled domains. adkim=s is recommended when not bulk-sending.MTA-STSEnabled and set to enforce.Implicit TLSMust be configured and enforced for every connection.Data Loss PreventionEnforce in line with the New Zealand Information Security Manual (NZISM) and Protective Security Requirements (PSR). Compliance Monitoring and Reporting The All of Government Service Delivery (AoGSD) team will be monitoring compliance with the framework. Monitoring will initially cover SPF, DMARC, and MTA-STS settings and will be expanded to include DKIM. Changes to these settings will be monitored, enabling reporting on email security compliance across all government agencies. Ongoing monitoring will highlight changes to domains, ensure new domains are set up with security in place, and monitor the implementation of future email security technologies.  Should compliance changes occur, such as an agency’s SPF record being changed from -all to ~all, this will be captured so that the AoGSD Security Team can investigate. They will then communicate directly with the agency to determine if an issue exists or if an error has occurred, reviewing each case individually. Deployment Checklist for NZ Government Compliance Enforce TLS 1.2 minimum, implicit TLS, MTA-STS & TLS-RPT SPF with -all DKIM on all outbound email DMARC p=reject  adkim=s where suitable For non-email/parked domains: SPF -all, empty DKIM, DMARC reject strict Compliance dashboard Inbound DMARC evaluation enforced DLP aligned with NZISM Start a Free Trial How EasyDMARC Can Help Government Agencies Comply EasyDMARC provides a comprehensive email security solution that simplifies the deployment and ongoing management of DNS-based email security protocols like SPF, DKIM, and DMARC with reporting. Our platform offers automated checks, real-time monitoring, and a guided setup to help government organizations quickly reach compliance. 1. TLS-RPT / MTA-STS audit EasyDMARC enables you to enable the Managed MTA-STS and TLS-RPT option with a single click. We provide the required DNS records and continuously monitor them for issues, delivering reports on TLS negotiation problems. This helps agencies ensure secure email transmission and quickly detect delivery or encryption failures. Note: In this screenshot, you can see how to deploy MTA-STS and TLS Reporting by adding just three CNAME records provided by EasyDMARC. It’s recommended to start in “testing” mode, evaluate the TLS-RPT reports, and then gradually switch your MTA-STS policy to “enforce”. The process is simple and takes just a few clicks. As shown above, EasyDMARC parses incoming TLS reports into a centralized dashboard, giving you clear visibility into delivery and encryption issues across all sending sources. 2. SPF with “-all”In the EasyDARC platform, you can run the SPF Record Generator to create a compliant record. Publish your v=spf1 record with “-all” to enforce a hard fail for unauthorized senders and prevent spoofed emails from passing SPF checks. This strengthens your domain’s protection against impersonation. Note: It is highly recommended to start adjusting your SPF record only after you begin receiving DMARC reports and identifying your legitimate email sources. As we’ll explain in more detail below, both SPF and DKIM should be adjusted after you gain visibility through reports. Making changes without proper visibility can lead to false positives, misconfigurations, and potential loss of legitimate emails. That’s why the first step should always be setting DMARC to p=none, receiving reports, analyzing them, and then gradually fixing any SPF or DKIM issues. 3. DKIM on all outbound email DKIM must be configured for all email sources sending emails on behalf of your domain. This is critical, as DKIM plays a bigger role than SPF when it comes to building domain reputation, surviving auto-forwarding, mailing lists, and other edge cases. As mentioned above, DMARC reports provide visibility into your email sources, allowing you to implement DKIM accordingly (see first screenshot). If you’re using third-party services like Google Workspace, Microsoft 365, or Mimecast, you’ll need to retrieve the public DKIM key from your provider’s admin interface (see second screenshot). EasyDMARC maintains a backend directory of over 1,400 email sources. We also give you detailed guidance on how to configure SPF and DKIM correctly for major ESPs.  Note: At the end of this article, you’ll find configuration links for well-known ESPs like Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid – helping you avoid common misconfigurations and get aligned with SGE requirements. If you’re using a dedicated MTA (e.g., Postfix), DKIM must be implemented manually. EasyDMARC’s DKIM Record Generator lets you generate both public and private keys for your server. The private key is stored on your MTA, while the public key must be published in your DNS (see third and fourth screenshots). 4. DMARC p=reject rollout As mentioned in previous points, DMARC reporting is the first and most important step on your DMARC enforcement journey. Always start with a p=none policy and configure RUA reports to be sent to EasyDMARC. Use the report insights to identify and fix SPF and DKIM alignment issues, then gradually move to p=quarantine and finally p=reject once all legitimate email sources have been authenticated.  This phased approach ensures full protection against domain spoofing without risking legitimate email delivery. 5. adkim Strict Alignment Check This strict alignment check is not always applicable, especially if you’re using third-party bulk ESPs, such as Sendgrid, that require you to set DKIM on a subdomain level. You can set adkim=s in your DMARC TXT record, or simply enable strict mode in EasyDMARC’s Managed DMARC settings. This ensures that only emails with a DKIM signature that exactly match your domain pass alignment, adding an extra layer of protection against domain spoofing. But only do this if you are NOT a bulk sender. 6. Securing Non-Email Enabled Domains The purpose of deploying email security to non-email-enabled domains, or parked domains, is to prevent messages being spoofed from that domain. This requirement remains even if the root-level domain has SP=reject set within its DMARC record. Under this new framework, you must bulk import and mark parked domains as “Parked.” Crucially, this requires adjusting SPF settings to an empty record, setting DMARC to p=reject, and ensuring an empty DKIM record is in place: • SPF record: “v=spf1 -all”. • Wildcard DKIM record with empty public key.• DMARC record: “v=DMARC1;p=reject;adkim=s;aspf=s;rua=mailto:…”. EasyDMARC allows you to add and label parked domains for free. This is important because it helps you monitor any activity from these domains and ensure they remain protected with a strict DMARC policy of p=reject. 7. Compliance Dashboard Use EasyDMARC’s Domain Scanner to assess the security posture of each domain with a clear compliance score and risk level. The dashboard highlights configuration gaps and guides remediation steps, helping government agencies stay on track toward full compliance with the SGE Framework. 8. Inbound DMARC Evaluation Enforced You don’t need to apply any changes if you’re using Google Workspace, Microsoft 365, or other major mailbox providers. Most of them already enforce DMARC evaluation on incoming emails. However, some legacy Microsoft 365 setups may still quarantine emails that fail DMARC checks, even when the sending domain has a p=reject policy, instead of rejecting them. This behavior can be adjusted directly from your Microsoft Defender portal. Read more about this in our step-by-step guide on how to set up SPF, DKIM, and DMARC from Microsoft Defender. If you’re using a third-party mail provider that doesn’t enforce having a DMARC policy for incoming emails, which is rare, you’ll need to contact their support to request a configuration change. 9. Data Loss Prevention Aligned with NZISM The New Zealand Information Security Manual (NZISM) is the New Zealand Government’s manual on information assurance and information systems security. It includes guidance on data loss prevention (DLP), which must be followed to be aligned with the SEG. Need Help Setting up SPF and DKIM for your Email Provider? Setting up SPF and DKIM for different ESPs often requires specific configurations. Some providers require you to publish SPF and DKIM on a subdomain, while others only require DKIM, or have different formatting rules. We’ve simplified all these steps to help you avoid misconfigurations that could delay your DMARC enforcement, or worse, block legitimate emails from reaching your recipients. Below you’ll find comprehensive setup guides for Google Workspace, Microsoft 365, Zoho Mail, Amazon SES, and SendGrid. You can also explore our full blog section that covers setup instructions for many other well-known ESPs. Remember, all this information is reflected in your DMARC aggregate reports. These reports give you live visibility into your outgoing email ecosystem, helping you analyze and fix any issues specific to a given provider. Here are our step-by-step guides for the most common platforms: Google Workspace Microsoft 365 These guides will help ensure your DNS records are configured correctly as part of the Secure Government Email (SGE) Framework rollout. Meet New Government Email Security Standards With EasyDMARC New Zealand’s SEG Framework sets a clear path for government agencies to enhance their email security by October 2025. With EasyDMARC, you can meet these technical requirements efficiently and with confidence. From protocol setup to continuous monitoring and compliance tracking, EasyDMARC streamlines the entire process, ensuring strong protection against spoofing, phishing, and data loss while simplifying your transition from SEEMail.
    0 Σχόλια 0 Μοιράστηκε
  • How AI is reshaping the future of healthcare and medical research

    Transcript       
    PETER LEE: “In ‘The Little Black Bag,’ a classic science fiction story, a high-tech doctor’s kit of the future is accidentally transported back to the 1950s, into the shaky hands of a washed-up, alcoholic doctor. The ultimate medical tool, it redeems the doctor wielding it, allowing him to practice gratifyingly heroic medicine. … The tale ends badly for the doctor and his treacherous assistant, but it offered a picture of how advanced technology could transform medicine—powerful when it was written nearly 75 years ago and still so today. What would be the Al equivalent of that little black bag? At this moment when new capabilities are emerging, how do we imagine them into medicine?”          
    This is The AI Revolution in Medicine, Revisited. I’m your host, Peter Lee.   
    Shortly after OpenAI’s GPT-4 was publicly released, Carey Goldberg, Dr. Zak Kohane, and I published The AI Revolution in Medicine to help educate the world of healthcare and medical research about the transformative impact this new generative AI technology could have. But because we wrote the book when GPT-4 was still a secret, we had to speculate. Now, two years later, what did we get right, and what did we get wrong?    
    In this series, we’ll talk to clinicians, patients, hospital administrators, and others to understand the reality of AI in the field and where we go from here.  The book passage I read at the top is from “Chapter 10: The Big Black Bag.” 
    In imagining AI in medicine, Carey, Zak, and I included in our book two fictional accounts. In the first, a medical resident consults GPT-4 on her personal phone as the patient in front of her crashes. Within seconds, it offers an alternate response based on recent literature. In the second account, a 90-year-old woman with several chronic conditions is living independently and receiving near-constant medical support from an AI aide.   
    In our conversations with the guests we’ve spoken to so far, we’ve caught a glimpse of these predicted futures, seeing how clinicians and patients are actually using AI today and how developers are leveraging the technology in the healthcare products and services they’re creating. In fact, that first fictional account isn’t so fictional after all, as most of the doctors in the real world actually appear to be using AI at least occasionally—and sometimes much more than occasionally—to help in their daily clinical work. And as for the second fictional account, which is more of a science fiction account, it seems we are indeed on the verge of a new way of delivering and receiving healthcare, though the future is still very much open. 
    As we continue to examine the current state of AI in healthcare and its potential to transform the field, I’m pleased to welcome Bill Gates and Sébastien Bubeck.  
    Bill may be best known as the co-founder of Microsoft, having created the company with his childhood friend Paul Allen in 1975. He’s now the founder of Breakthrough Energy, which aims to advance clean energy innovation, and TerraPower, a company developing groundbreaking nuclear energy and science technologies. He also chairs the world’s largest philanthropic organization, the Gates Foundation, and focuses on solving a variety of health challenges around the globe and here at home. 
    Sébastien is a research lead at OpenAI. He was previously a distinguished scientist, vice president of AI, and a colleague of mine here at Microsoft, where his work included spearheading the development of the family of small language models known as Phi. While at Microsoft, he also coauthored the discussion-provoking 2023 paper “Sparks of Artificial General Intelligence,” which presented the results of early experiments with GPT-4 conducted by a small team from Microsoft Research.     
    Here’s my conversation with Bill Gates and Sébastien Bubeck. 
    LEE: Bill, welcome. 
    BILL GATES: Thank you. 
    LEE: Seb … 
    SÉBASTIEN BUBECK: Yeah. Hi, hi, Peter. Nice to be here. 
    LEE: You know, one of the things that I’ve been doing just to get the conversation warmed up is to talk about origin stories, and what I mean about origin stories is, you know, what was the first contact that you had with large language models or the concept of generative AI that convinced you or made you think that something really important was happening? 
    And so, Bill, I think I’ve heard the story about, you know, the time when the OpenAI folks—Sam Altman, Greg Brockman, and others—showed you something, but could we hear from you what those early encounters were like and what was going through your mind?  
    GATES: Well, I’d been visiting OpenAI soon after it was created to see things like GPT-2 and to see the little arm they had that was trying to match human manipulation and, you know, looking at their games like Dota that they were trying to get as good as human play. And honestly, I didn’t think the language model stuff they were doing, even when they got to GPT-3, would show the ability to learn, you know, in the same sense that a human reads a biology book and is able to take that knowledge and access it not only to pass a test but also to create new medicines. 
    And so my challenge to them was that if their LLM could get a five on the advanced placement biology test, then I would say, OK, it took biologic knowledge and encoded it in an accessible way and that I didn’t expect them to do that very quickly but it would be profound.  
    And it was only about six months after I challenged them to do that, that an early version of GPT-4 they brought up to a dinner at my house, and in fact, it answered most of the questions that night very well. The one it got totally wrong, we were … because it was so good, we kept thinking, Oh, we must be wrong. It turned out it was a math weaknessthat, you know, we later understood that that was an area of, weirdly, of incredible weakness of those early models. But, you know, that was when I realized, OK, the age of cheap intelligence was at its beginning. 
    LEE: Yeah. So I guess it seems like you had something similar to me in that my first encounters, I actually harbored some skepticism. Is it fair to say you were skeptical before that? 
    GATES: Well, the idea that we’ve figured out how to encode and access knowledge in this very deep sense without even understanding the nature of the encoding, … 
    LEE: Right.  
    GATES: … that is a bit weird.  
    LEE: Yeah. 
    GATES: We have an algorithm that creates the computation, but even say, OK, where is the president’s birthday stored in there? Where is this fact stored in there? The fact that even now when we’re playing around, getting a little bit more sense of it, it’s opaque to us what the semantic encoding is, it’s, kind of, amazing to me. I thought the invention of knowledge storage would be an explicit way of encoding knowledge, not an implicit statistical training. 
    LEE: Yeah, yeah. All right. So, Seb, you know, on this same topic, you know, I got—as we say at Microsoft—I got pulled into the tent. 
    BUBECK: Yes.  
    LEE: Because this was a very secret project. And then, um, I had the opportunity to select a small number of researchers in MSRto join and start investigating this thing seriously. And the first person I pulled in was you. 
    BUBECK: Yeah. 
    LEE: And so what were your first encounters? Because I actually don’t remember what happened then. 
    BUBECK: Oh, I remember it very well.My first encounter with GPT-4 was in a meeting with the two of you, actually. But my kind of first contact, the first moment where I realized that something was happening with generative AI, was before that. And I agree with Bill that I also wasn’t too impressed by GPT-3. 
    I though that it was kind of, you know, very naturally mimicking the web, sort of parroting what was written there in a nice way. Still in a way which seemed very impressive. But it wasn’t really intelligent in any way. But shortly after GPT-3, there was a model before GPT-4 that really shocked me, and this was the first image generation model, DALL-E 1. 
    So that was in 2021. And I will forever remember the press release of OpenAI where they had this prompt of an avocado chair and then you had this image of the avocado chair.And what really shocked me is that clearly the model kind of “understood” what is a chair, what is an avocado, and was able to merge those concepts. 
    So this was really, to me, the first moment where I saw some understanding in those models.  
    LEE: So this was, just to get the timing right, that was before I pulled you into the tent. 
    BUBECK: That was before. That was like a year before. 
    LEE: Right.  
    BUBECK: And now I will tell you how, you know, we went from that moment to the meeting with the two of you and GPT-4. 
    So once I saw this kind of understanding, I thought, OK, fine. It understands concept, but it’s still not able to reason. It cannot—as, you know, Bill was saying—it cannot learn from your document. It cannot reason.  
    So I set out to try to prove that. You know, this is what I was in the business of at the time, trying to prove things in mathematics. So I was trying to prove that basically autoregressive transformers could never reason. So I was trying to prove this. And after a year of work, I had something reasonable to show. And so I had the meeting with the two of you, and I had this example where I wanted to say, there is no way that an LLM is going to be able to do x. 
    And then as soon as I … I don’t know if you remember, Bill. But as soon as I said that, you said, oh, but wait a second. I had, you know, the OpenAI crew at my house recently, and they showed me a new model. Why don’t we ask this new model this question?  
    LEE: Yeah.
    BUBECK: And we did, and it solved it on the spot. And that really, honestly, just changed my life. Like, you know, I had been working for a year trying to say that this was impossible. And just right there, it was shown to be possible.  
    LEE:One of the very first things I got interested in—because I was really thinking a lot about healthcare—was healthcare and medicine. 
    And I don’t know if the two of you remember, but I ended up doing a lot of tests. I ran through, you know, step one and step two of the US Medical Licensing Exam. Did a whole bunch of other things. I wrote this big report. It was, you know, I can’t remember … a couple hundred pages.  
    And I needed to share this with someone. I didn’t … there weren’t too many people I could share it with. So I sent, I think, a copy to you, Bill. Sent a copy to you, Seb.  
    I hardly slept for about a week putting that report together. And, yeah, and I kept working on it. But I was far from alone. I think everyone who was in the tent, so to speak, in those early days was going through something pretty similar. All right. So I think … of course, a lot of what I put in the report also ended up being examples that made it into the book. 
    But the main purpose of this conversation isn’t to reminisce aboutor indulge in those reminiscences but to talk about what’s happening in healthcare and medicine. And, you know, as I said, we wrote this book. We did it very, very quickly. Seb, you helped. Bill, you know, you provided a review and some endorsements. 
    But, you know, honestly, we didn’t know what we were talking about because no one had access to this thing. And so we just made a bunch of guesses. So really, the whole thing I wanted to probe with the two of you is, now with two years of experience out in the world, what, you know, what do we think is happening today? 
    You know, is AI actually having an impact, positive or negative, on healthcare and medicine? And what do we now think is going to happen in the next two years, five years, or 10 years? And so I realize it’s a little bit too abstract to just ask it that way. So let me just try to narrow the discussion and guide us a little bit.  
    Um, the kind of administrative and clerical work, paperwork, around healthcare—and we made a lot of guesses about that—that appears to be going well, but, you know, Bill, I know we’ve discussed that sometimes that you think there ought to be a lot more going on. Do you have a viewpoint on how AI is actually finding its way into reducing paperwork? 
    GATES: Well, I’m stunned … I don’t think there should be a patient-doctor meeting where the AI is not sitting in and both transcribing, offering to help with the paperwork, and even making suggestions, although the doctor will be the one, you know, who makes the final decision about the diagnosis and whatever prescription gets done.  
    It’s so helpful. You know, when that patient goes home and their, you know, son who wants to understand what happened has some questions, that AI should be available to continue that conversation. And the way you can improve that experience and streamline things and, you know, involve the people who advise you. I don’t understand why that’s not more adopted, because there you still have the human in the loop making that final decision. 
    But even for, like, follow-up calls to make sure the patient did things, to understand if they have concerns and knowing when to escalate back to the doctor, the benefit is incredible. And, you know, that thing is ready for prime time. That paradigm is ready for prime time, in my view. 
    LEE: Yeah, there are some good products, but it seems like the number one use right now—and we kind of got this from some of the previous guests in previous episodes—is the use of AI just to respond to emails from patients.Does that make sense to you? 
    BUBECK: Yeah. So maybe I want to second what Bill was saying but maybe take a step back first. You know, two years ago, like, the concept of clinical scribes, which is one of the things that we’re talking about right now, it would have sounded, in fact, it sounded two years ago, borderline dangerous. Because everybody was worried about hallucinations. What happened if you have this AI listening in and then it transcribes, you know, something wrong? 
    Now, two years later, I think it’s mostly working. And in fact, it is not yet, you know, fully adopted. You’re right. But it is in production. It is used, you know, in many, many places. So this rate of progress is astounding because it wasn’t obvious that we would be able to overcome those obstacles of hallucination. It’s not to say that hallucinations are fully solved. In the case of the closed system, they are.  
    Now, I think more generally what’s going on in the background is that there is something that we, that certainly I, underestimated, which is this management overhead. So I think the reason why this is not adopted everywhere is really a training and teaching aspect. People need to be taught, like, those systems, how to interact with them. 
    And one example that I really like, a study that recently appeared where they tried to use ChatGPT for diagnosis and they were comparing doctors without and with ChatGPT. And the amazing thing … so this was a set of cases where the accuracy of the doctors alone was around 75%. ChatGPT alone was 90%. So that’s already kind of mind blowing. But then the kicker is that doctors with ChatGPT was 80%.  
    Intelligence alone is not enough. It’s also how it’s presented, how you interact with it. And ChatGPT, it’s an amazing tool. Obviously, I absolutely love it. But it’s not … you don’t want a doctor to have to type in, you know, prompts and use it that way. 
    It should be, as Bill was saying, kind of running continuously in the background, sending you notifications. And you have to be really careful of the rate at which those notifications are being sent. Because if they are too frequent, then the doctor will learn to ignore them. So you have to … all of those things matter, in fact, at least as much as the level of intelligence of the machine. 
    LEE: One of the things I think about, Bill, in that scenario that you described, doctors do some thinking about the patient when they write the note. So, you know, I’m always a little uncertain whether it’s actually … you know, you wouldn’t necessarily want to fully automate this, I don’t think. Or at least there needs to be some prompt to the doctor to make sure that the doctor puts some thought into what happened in the encounter with the patient. Does that make sense to you at all? 
    GATES: At this stage, you know, I’d still put the onus on the doctor to write the conclusions and the summary and not delegate that. 
    The tradeoffs you make a little bit are somewhat dependent on the situation you’re in. If you’re in Africa,
    So, yes, the doctor’s still going to have to do a lot of work, but just the quality of letting the patient and the people around them interact and ask questions and have things explained, that alone is such a quality improvement. It’s mind blowing.  
    LEE: So since you mentioned, you know, Africa—and, of course, this touches on the mission and some of the priorities of the Gates Foundation and this idea of democratization of access to expert medical care—what’s the most interesting stuff going on right now? Are there people and organizations or technologies that are impressing you or that you’re tracking? 
    GATES: Yeah. So the Gates Foundation has given out a lot of grants to people in Africa doing education, agriculture but more healthcare examples than anything. And the way these things start off, they often start out either being patient-centric in a narrow situation, like, OK, I’m a pregnant woman; talk to me. Or, I have infectious disease symptoms; talk to me. Or they’re connected to a health worker where they’re helping that worker get their job done. And we have lots of pilots out, you know, in both of those cases.  
    The dream would be eventually to have the thing the patient consults be so broad that it’s like having a doctor available who understands the local things.  
    LEE: Right.  
    GATES: We’re not there yet. But over the next two or three years, you know, particularly given the worsening financial constraints against African health systems, where the withdrawal of money has been dramatic, you know, figuring out how to take this—what I sometimes call “free intelligence”—and build a quality health system around that, we will have to be more radical in low-income countries than any rich country is ever going to be.  
    LEE: Also, there’s maybe a different regulatory environment, so some of those things maybe are easier? Because right now, I think the world hasn’t figured out how to and whether to regulate, let’s say, an AI that might give a medical diagnosis or write a prescription for a medication. 
    BUBECK: Yeah. I think one issue with this, and it’s also slowing down the deployment of AI in healthcare more generally, is a lack of proper benchmark. Because, you know, you were mentioning the USMLE, for example. That’s a great test to test human beings and their knowledge of healthcare and medicine. But it’s not a great test to give to an AI. 
    It’s not asking the right questions. So finding what are the right questions to test whether an AI system is ready to give diagnosis in a constrained setting, that’s a very, very important direction, which to my surprise, is not yet accelerating at the rate that I was hoping for. 
    LEE: OK, so that gives me an excuse to get more now into the core AI tech because something I’ve discussed with both of you is this issue of what are the right tests. And you both know the very first test I give to any new spin of an LLM is I present a patient, the results—a mythical patient—the results of my physical exam, my mythical physical exam. Maybe some results of some initial labs. And then I present or propose a differential diagnosis. And if you’re not in medicine, a differential diagnosis you can just think of as a prioritized list of the possible diagnoses that fit with all that data. And in that proposed differential, I always intentionally make two mistakes. 
    I make a textbook technical error in one of the possible elements of the differential diagnosis, and I have an error of omission. And, you know, I just want to know, does the LLM understand what I’m talking about? And all the good ones out there do now. But then I want to know, can it spot the errors? And then most importantly, is it willing to tell me I’m wrong, that I’ve made a mistake?  
    That last piece seems really hard for AI today. And so let me ask you first, Seb, because at the time of this taping, of course, there was a new spin of GPT-4o last week that became overly sycophantic. In other words, it was actually prone in that test of mine not only to not tell me I’m wrong, but it actually praised me for the creativity of my differential.What’s up with that? 
    BUBECK: Yeah, I guess it’s a testament to the fact that training those models is still more of an art than a science. So it’s a difficult job. Just to be clear with the audience, we have rolled back thatversion of GPT-4o, so now we don’t have the sycophant version out there. 
    Yeah, no, it’s a really difficult question. It has to do … as you said, it’s very technical. It has to do with the post-training and how, like, where do you nudge the model? So, you know, there is this very classical by now technique called RLHF, where you push the model in the direction of a certain reward model. So the reward model is just telling the model, you know, what behavior is good, what behavior is bad. 
    But this reward model is itself an LLM, and, you know, Bill was saying at the very beginning of the conversation that we don’t really understand how those LLMs deal with concepts like, you know, where is the capital of France located? Things like that. It is the same thing for this reward model. We don’t know why it says that it prefers one output to another, and whether this is correlated with some sycophancy is, you know, something that we discovered basically just now. That if you push too hard in optimization on this reward model, you will get a sycophant model. 
    So it’s kind of … what I’m trying to say is we became too good at what we were doing, and we ended up, in fact, in a trap of the reward model. 
    LEE: I mean, you do want … it’s a difficult balance because you do want models to follow your desires and … 
    BUBECK: It’s a very difficult, very difficult balance. 
    LEE: So this brings up then the following question for me, which is the extent to which we think we’ll need to have specially trained models for things. So let me start with you, Bill. Do you have a point of view on whether we will need to, you know, quote-unquote take AI models to med school? Have them specially trained? Like, if you were going to deploy something to give medical care in underserved parts of the world, do we need to do something special to create those models? 
    GATES: We certainly need to teach them the African languages and the unique dialects so that the multimedia interactions are very high quality. We certainly need to teach them the disease prevalence and unique disease patterns like, you know, neglected tropical diseases and malaria. So we need to gather a set of facts that somebody trying to go for a US customer base, you know, wouldn’t necessarily have that in there. 
    Those two things are actually very straightforward because the additional training time is small. I’d say for the next few years, we’ll also need to do reinforcement learning about the context of being a doctor and how important certain behaviors are. Humans learn over the course of their life to some degree that, I’m in a different context and the way I behave in terms of being willing to criticize or be nice, you know, how important is it? Who’s here? What’s my relationship to them?  
    Right now, these machines don’t have that broad social experience. And so if you know it’s going to be used for health things, a lot of reinforcement learning of the very best humans in that context would still be valuable. Eventually, the models will, having read all the literature of the world about good doctors, bad doctors, it’ll understand as soon as you say, “I want you to be a doctor diagnosing somebody.” All of the implicit reinforcement that fits that situation, you know, will be there.
    LEE: Yeah.
    GATES: And so I hope three years from now, we don’t have to do that reinforcement learning. But today, for any medical context, you would want a lot of data to reinforce tone, willingness to say things when, you know, there might be something significant at stake. 
    LEE: Yeah. So, you know, something Bill said, kind of, reminds me of another thing that I think we missed, which is, the context also … and the specialization also pertains to different, I guess, what we still call “modes,” although I don’t know if the idea of multimodal is the same as it was two years ago. But, you know, what do you make of all of the hubbub around—in fact, within Microsoft Research, this is a big deal, but I think we’re far from alone—you know, medical images and vision, video, proteins and molecules, cell, you know, cellular data and so on. 
    BUBECK: Yeah. OK. So there is a lot to say to everything … to the last, you know, couple of minutes. Maybe on the specialization aspect, you know, I think there is, hiding behind this, a really fundamental scientific question of whether eventually we have a singular AGIthat kind of knows everything and you can just put, you know, explain your own context and it will just get it and understand everything. 
    That’s one vision. I have to say, I don’t particularly believe in this vision. In fact, we humans are not like that at all. I think, hopefully, we are general intelligences, yet we have to specialize a lot. And, you know, I did myself a lot of RL, reinforcement learning, on mathematics. Like, that’s what I did, you know, spent a lot of time doing that. And I didn’t improve on other aspects. You know, in fact, I probably degraded in other aspects.So it’s … I think it’s an important example to have in mind. 
    LEE: I think I might disagree with you on that, though, because, like, doesn’t a model have to see both good science and bad science in order to be able to gain the ability to discern between the two? 
    BUBECK: Yeah, no, that absolutely. I think there is value in seeing the generality, in having a very broad base. But then you, kind of, specialize on verticals. And this is where also, you know, open-weights model, which we haven’t talked about yet, are really important because they allow you to provide this broad base to everyone. And then you can specialize on top of it. 
    LEE: So we have about three hours of stuff to talk about, but our time is actually running low.
    BUBECK: Yes, yes, yes.  
    LEE: So I think I want … there’s a more provocative question. It’s almost a silly question, but I need to ask it of the two of you, which is, is there a future, you know, where AI replaces doctors or replaces, you know, medical specialties that we have today? So what does the world look like, say, five years from now? 
    GATES: Well, it’s important to distinguish healthcare discovery activity from healthcare delivery activity. We focused mostly on delivery. I think it’s very much within the realm of possibility that the AI is not only accelerating healthcare discovery but substituting for a lot of the roles of, you know, I’m an organic chemist, or I run various types of assays. I can see those, which are, you know, testable-output-type jobs but with still very high value, I can see, you know, some replacement in those areas before the doctor.  
    The doctor, still understanding the human condition and long-term dialogues, you know, they’ve had a lifetime of reinforcement of that, particularly when you get into areas like mental health. So I wouldn’t say in five years, either people will choose to adopt it, but it will be profound that there’ll be this nearly free intelligence that can do follow-up, that can help you, you know, make sure you went through different possibilities. 
    And so I’d say, yes, we’ll have doctors, but I’d say healthcare will be massively transformed in its quality and in efficiency by AI in that time period. 
    LEE: Is there a comparison, useful comparison, say, between doctors and, say, programmers, computer programmers, or doctors and, I don’t know, lawyers? 
    GATES: Programming is another one that has, kind of, a mathematical correctness to it, you know, and so the objective function that you’re trying to reinforce to, as soon as you can understand the state machines, you can have something that’s “checkable”; that’s correct. So I think programming, you know, which is weird to say, that the machine will beat us at most programming tasks before we let it take over roles that have deep empathy, you know, physical presence and social understanding in them. 
    LEE: Yeah. By the way, you know, I fully expect in five years that AI will produce mathematical proofs that are checkable for validity, easily checkable, because they’ll be written in a proof-checking language like Lean or something but will be so complex that no human mathematician can understand them. I expect that to happen.  
    I can imagine in some fields, like cellular biology, we could have the same situation in the future because the molecular pathways, the chemistry, biochemistry of human cells or living cells is as complex as any mathematics, and so it seems possible that we may be in a state where in wet lab, we see, Oh yeah, this actually works, but no one can understand why. 
    BUBECK: Yeah, absolutely. I mean, I think I really agree with Bill’s distinction of the discovery and the delivery, and indeed, the discovery’s when you can check things, and at the end, there is an artifact that you can verify. You know, you can run the protocol in the wet lab and seeproduced what you wanted. So I absolutely agree with that.  
    And in fact, you know, we don’t have to talk five years from now. I don’t know if you know, but just recently, there was a paper that was published on a scientific discovery using o3- mini. So this is really amazing. And, you know, just very quickly, just so people know, it was about this statistical physics model, the frustrated Potts model, which has to do with coloring, and basically, the case of three colors, like, more than two colors was open for a long time, and o3 was able to reduce the case of three colors to two colors.  
    LEE: Yeah. 
    BUBECK: Which is just, like, astounding. And this is not … this is now. This is happening right now. So this is something that I personally didn’t expect it would happen so quickly, and it’s due to those reasoning models.  
    Now, on the delivery side, I would add something more to it for the reason why doctors and, in fact, lawyers and coders will remain for a long time, and it’s because we still don’t understand how those models generalize. Like, at the end of the day, we are not able to tell you when they are confronted with a really new, novel situation, whether they will work or not. 
    Nobody is able to give you that guarantee. And I think until we understand this generalization better, we’re not going to be willing to just let the system in the wild without human supervision. 
    LEE: But don’t human doctors, human specialists … so, for example, a cardiologist sees a patient in a certain way that a nephrologist … 
    BUBECK: Yeah.
    LEE: … or an endocrinologist might not.
    BUBECK: That’s right. But another cardiologist will understand and, kind of, expect a certain level of generalization from their peer. And this, we just don’t have it with AI models. Now, of course, you’re exactly right. That generalization is also hard for humans. Like, if you have a human trained for one task and you put them into another task, then you don’t … you often don’t know.
    LEE: OK. You know, the podcast is focused on what’s happened over the last two years. But now, I’d like one provocative prediction about what you think the world of AI and medicine is going to be at some point in the future. You pick your timeframe. I don’t care if it’s two years or 20 years from now, but, you know, what do you think will be different about AI in medicine in that future than today? 
    BUBECK: Yeah, I think the deployment is going to accelerate soon. Like, we’re really not missing very much. There is this enormous capability overhang. Like, even if progress completely stopped, with current systems, we can do a lot more than what we’re doing right now. So I think this will … this has to be realized, you know, sooner rather than later. 
    And I think it’s probably dependent on these benchmarks and proper evaluation and tying this with regulation. So these are things that take time in human society and for good reason. But now we already are at two years; you know, give it another two years and it should be really …  
    LEE: Will AI prescribe your medicines? Write your prescriptions? 
    BUBECK: I think yes. I think yes. 
    LEE: OK. Bill? 
    GATES: Well, I think the next two years, we’ll have massive pilots, and so the amount of use of the AI, still in a copilot-type mode, you know, we should get millions of patient visits, you know, both in general medicine and in the mental health side, as well. And I think that’s going to build up both the data and the confidence to give the AI some additional autonomy. You know, are you going to let it talk to you at night when you’re panicked about your mental health with some ability to escalate?
    And, you know, I’ve gone so far as to tell politicians with national health systems that if they deploy AI appropriately, that the quality of care, the overload of the doctors, the improvement in the economics will be enough that their voters will be stunned because they just don’t expect this, and, you know, they could be reelectedjust on this one thing of fixing what is a very overloaded and economically challenged health system in these rich countries. 
    You know, my personal role is going to be to make sure that in the poorer countries, there isn’t some lag; in fact, in many cases, that we’ll be more aggressive because, you know, we’re comparing to having no access to doctors at all. And, you know, so I think whether it’s India or Africa, there’ll be lessons that are globally valuable because we need medical intelligence. And, you know, thank god AI is going to provide a lot of that. 
    LEE: Well, on that optimistic note, I think that’s a good way to end. Bill, Seb, really appreciate all of this.  
    I think the most fundamental prediction we made in the book is that AI would actually find its way into the practice of medicine, and I think that that at least has come true, maybe in different ways than we expected, but it’s come true, and I think it’ll only accelerate from here. So thanks again, both of you.  
    GATES: Yeah. Thanks, you guys. 
    BUBECK: Thank you, Peter. Thanks, Bill. 
    LEE: I just always feel such a sense of privilege to have a chance to interact and actually work with people like Bill and Sébastien.   
    With Bill, I’m always amazed at how practically minded he is. He’s really thinking about the nuts and bolts of what AI might be able to do for people, and his thoughts about underserved parts of the world, the idea that we might actually be able to empower people with access to expert medical knowledge, I think is both inspiring and amazing.  
    And then, Seb, Sébastien Bubeck, he’s just absolutely a brilliant mind. He has a really firm grip on the deep mathematics of artificial intelligence and brings that to bear in his research and development work. And where that mathematics takes him isn’t just into the nuts and bolts of algorithms but into philosophical questions about the nature of intelligence.  
    One of the things that Sébastien brought up was the state of evaluation of AI systems. And indeed, he was fairly critical in our conversation. But of course, the world of AI research and development is just moving so fast, and indeed, since we recorded our conversation, OpenAI, in fact, released a new evaluation metric that is directly relevant to medical applications, and that is something called HealthBench. And Microsoft Research also released a new evaluation approach or process called ADeLe.  
    HealthBench and ADeLe are examples of new approaches to evaluating AI models that are less about testing their knowledge and ability to pass multiple-choice exams and instead are evaluation approaches designed to assess how well AI models are able to complete tasks that actually arise every day in typical healthcare or biomedical research settings. These are examples of really important good work that speak to how well AI models work in the real world of healthcare and biomedical research and how well they can collaborate with human beings in those settings. 
    You know, I asked Bill and Seb to make some predictions about the future. You know, my own answer, I expect that we’re going to be able to use AI to change how we diagnose patients, change how we decide treatment options.  
    If you’re a doctor or a nurse and you encounter a patient, you’ll ask questions, do a physical exam, you know, call out for labs just like you do today, but then you’ll be able to engage with AI based on all of that data and just ask, you know, based on all the other people who have gone through the same experience, who have similar data, how were they diagnosed? How were they treated? What were their outcomes? And what does that mean for the patient I have right now? Some people call it the “patients like me” paradigm. And I think that’s going to become real because of AI within our lifetimes. That idea of really grounding the delivery in healthcare and medical practice through data and intelligence, I actually now don’t see any barriers to that future becoming real.  
    I’d like to extend another big thank you to Bill and Sébastien for their time. And to our listeners, as always, it’s a pleasure to have you along for the ride. I hope you’ll join us for our remaining conversations, as well as a second coauthor roundtable with Carey and Zak.  
    Until next time.  
    #how #reshaping #future #healthcare #medical
    How AI is reshaping the future of healthcare and medical research
    Transcript        PETER LEE: “In ‘The Little Black Bag,’ a classic science fiction story, a high-tech doctor’s kit of the future is accidentally transported back to the 1950s, into the shaky hands of a washed-up, alcoholic doctor. The ultimate medical tool, it redeems the doctor wielding it, allowing him to practice gratifyingly heroic medicine. … The tale ends badly for the doctor and his treacherous assistant, but it offered a picture of how advanced technology could transform medicine—powerful when it was written nearly 75 years ago and still so today. What would be the Al equivalent of that little black bag? At this moment when new capabilities are emerging, how do we imagine them into medicine?”           This is The AI Revolution in Medicine, Revisited. I’m your host, Peter Lee.    Shortly after OpenAI’s GPT-4 was publicly released, Carey Goldberg, Dr. Zak Kohane, and I published The AI Revolution in Medicine to help educate the world of healthcare and medical research about the transformative impact this new generative AI technology could have. But because we wrote the book when GPT-4 was still a secret, we had to speculate. Now, two years later, what did we get right, and what did we get wrong?     In this series, we’ll talk to clinicians, patients, hospital administrators, and others to understand the reality of AI in the field and where we go from here.  The book passage I read at the top is from “Chapter 10: The Big Black Bag.”  In imagining AI in medicine, Carey, Zak, and I included in our book two fictional accounts. In the first, a medical resident consults GPT-4 on her personal phone as the patient in front of her crashes. Within seconds, it offers an alternate response based on recent literature. In the second account, a 90-year-old woman with several chronic conditions is living independently and receiving near-constant medical support from an AI aide.    In our conversations with the guests we’ve spoken to so far, we’ve caught a glimpse of these predicted futures, seeing how clinicians and patients are actually using AI today and how developers are leveraging the technology in the healthcare products and services they’re creating. In fact, that first fictional account isn’t so fictional after all, as most of the doctors in the real world actually appear to be using AI at least occasionally—and sometimes much more than occasionally—to help in their daily clinical work. And as for the second fictional account, which is more of a science fiction account, it seems we are indeed on the verge of a new way of delivering and receiving healthcare, though the future is still very much open.  As we continue to examine the current state of AI in healthcare and its potential to transform the field, I’m pleased to welcome Bill Gates and Sébastien Bubeck.   Bill may be best known as the co-founder of Microsoft, having created the company with his childhood friend Paul Allen in 1975. He’s now the founder of Breakthrough Energy, which aims to advance clean energy innovation, and TerraPower, a company developing groundbreaking nuclear energy and science technologies. He also chairs the world’s largest philanthropic organization, the Gates Foundation, and focuses on solving a variety of health challenges around the globe and here at home.  Sébastien is a research lead at OpenAI. He was previously a distinguished scientist, vice president of AI, and a colleague of mine here at Microsoft, where his work included spearheading the development of the family of small language models known as Phi. While at Microsoft, he also coauthored the discussion-provoking 2023 paper “Sparks of Artificial General Intelligence,” which presented the results of early experiments with GPT-4 conducted by a small team from Microsoft Research.      Here’s my conversation with Bill Gates and Sébastien Bubeck.  LEE: Bill, welcome.  BILL GATES: Thank you.  LEE: Seb …  SÉBASTIEN BUBECK: Yeah. Hi, hi, Peter. Nice to be here.  LEE: You know, one of the things that I’ve been doing just to get the conversation warmed up is to talk about origin stories, and what I mean about origin stories is, you know, what was the first contact that you had with large language models or the concept of generative AI that convinced you or made you think that something really important was happening?  And so, Bill, I think I’ve heard the story about, you know, the time when the OpenAI folks—Sam Altman, Greg Brockman, and others—showed you something, but could we hear from you what those early encounters were like and what was going through your mind?   GATES: Well, I’d been visiting OpenAI soon after it was created to see things like GPT-2 and to see the little arm they had that was trying to match human manipulation and, you know, looking at their games like Dota that they were trying to get as good as human play. And honestly, I didn’t think the language model stuff they were doing, even when they got to GPT-3, would show the ability to learn, you know, in the same sense that a human reads a biology book and is able to take that knowledge and access it not only to pass a test but also to create new medicines.  And so my challenge to them was that if their LLM could get a five on the advanced placement biology test, then I would say, OK, it took biologic knowledge and encoded it in an accessible way and that I didn’t expect them to do that very quickly but it would be profound.   And it was only about six months after I challenged them to do that, that an early version of GPT-4 they brought up to a dinner at my house, and in fact, it answered most of the questions that night very well. The one it got totally wrong, we were … because it was so good, we kept thinking, Oh, we must be wrong. It turned out it was a math weaknessthat, you know, we later understood that that was an area of, weirdly, of incredible weakness of those early models. But, you know, that was when I realized, OK, the age of cheap intelligence was at its beginning.  LEE: Yeah. So I guess it seems like you had something similar to me in that my first encounters, I actually harbored some skepticism. Is it fair to say you were skeptical before that?  GATES: Well, the idea that we’ve figured out how to encode and access knowledge in this very deep sense without even understanding the nature of the encoding, …  LEE: Right.   GATES: … that is a bit weird.   LEE: Yeah.  GATES: We have an algorithm that creates the computation, but even say, OK, where is the president’s birthday stored in there? Where is this fact stored in there? The fact that even now when we’re playing around, getting a little bit more sense of it, it’s opaque to us what the semantic encoding is, it’s, kind of, amazing to me. I thought the invention of knowledge storage would be an explicit way of encoding knowledge, not an implicit statistical training.  LEE: Yeah, yeah. All right. So, Seb, you know, on this same topic, you know, I got—as we say at Microsoft—I got pulled into the tent.  BUBECK: Yes.   LEE: Because this was a very secret project. And then, um, I had the opportunity to select a small number of researchers in MSRto join and start investigating this thing seriously. And the first person I pulled in was you.  BUBECK: Yeah.  LEE: And so what were your first encounters? Because I actually don’t remember what happened then.  BUBECK: Oh, I remember it very well.My first encounter with GPT-4 was in a meeting with the two of you, actually. But my kind of first contact, the first moment where I realized that something was happening with generative AI, was before that. And I agree with Bill that I also wasn’t too impressed by GPT-3.  I though that it was kind of, you know, very naturally mimicking the web, sort of parroting what was written there in a nice way. Still in a way which seemed very impressive. But it wasn’t really intelligent in any way. But shortly after GPT-3, there was a model before GPT-4 that really shocked me, and this was the first image generation model, DALL-E 1.  So that was in 2021. And I will forever remember the press release of OpenAI where they had this prompt of an avocado chair and then you had this image of the avocado chair.And what really shocked me is that clearly the model kind of “understood” what is a chair, what is an avocado, and was able to merge those concepts.  So this was really, to me, the first moment where I saw some understanding in those models.   LEE: So this was, just to get the timing right, that was before I pulled you into the tent.  BUBECK: That was before. That was like a year before.  LEE: Right.   BUBECK: And now I will tell you how, you know, we went from that moment to the meeting with the two of you and GPT-4.  So once I saw this kind of understanding, I thought, OK, fine. It understands concept, but it’s still not able to reason. It cannot—as, you know, Bill was saying—it cannot learn from your document. It cannot reason.   So I set out to try to prove that. You know, this is what I was in the business of at the time, trying to prove things in mathematics. So I was trying to prove that basically autoregressive transformers could never reason. So I was trying to prove this. And after a year of work, I had something reasonable to show. And so I had the meeting with the two of you, and I had this example where I wanted to say, there is no way that an LLM is going to be able to do x.  And then as soon as I … I don’t know if you remember, Bill. But as soon as I said that, you said, oh, but wait a second. I had, you know, the OpenAI crew at my house recently, and they showed me a new model. Why don’t we ask this new model this question?   LEE: Yeah. BUBECK: And we did, and it solved it on the spot. And that really, honestly, just changed my life. Like, you know, I had been working for a year trying to say that this was impossible. And just right there, it was shown to be possible.   LEE:One of the very first things I got interested in—because I was really thinking a lot about healthcare—was healthcare and medicine.  And I don’t know if the two of you remember, but I ended up doing a lot of tests. I ran through, you know, step one and step two of the US Medical Licensing Exam. Did a whole bunch of other things. I wrote this big report. It was, you know, I can’t remember … a couple hundred pages.   And I needed to share this with someone. I didn’t … there weren’t too many people I could share it with. So I sent, I think, a copy to you, Bill. Sent a copy to you, Seb.   I hardly slept for about a week putting that report together. And, yeah, and I kept working on it. But I was far from alone. I think everyone who was in the tent, so to speak, in those early days was going through something pretty similar. All right. So I think … of course, a lot of what I put in the report also ended up being examples that made it into the book.  But the main purpose of this conversation isn’t to reminisce aboutor indulge in those reminiscences but to talk about what’s happening in healthcare and medicine. And, you know, as I said, we wrote this book. We did it very, very quickly. Seb, you helped. Bill, you know, you provided a review and some endorsements.  But, you know, honestly, we didn’t know what we were talking about because no one had access to this thing. And so we just made a bunch of guesses. So really, the whole thing I wanted to probe with the two of you is, now with two years of experience out in the world, what, you know, what do we think is happening today?  You know, is AI actually having an impact, positive or negative, on healthcare and medicine? And what do we now think is going to happen in the next two years, five years, or 10 years? And so I realize it’s a little bit too abstract to just ask it that way. So let me just try to narrow the discussion and guide us a little bit.   Um, the kind of administrative and clerical work, paperwork, around healthcare—and we made a lot of guesses about that—that appears to be going well, but, you know, Bill, I know we’ve discussed that sometimes that you think there ought to be a lot more going on. Do you have a viewpoint on how AI is actually finding its way into reducing paperwork?  GATES: Well, I’m stunned … I don’t think there should be a patient-doctor meeting where the AI is not sitting in and both transcribing, offering to help with the paperwork, and even making suggestions, although the doctor will be the one, you know, who makes the final decision about the diagnosis and whatever prescription gets done.   It’s so helpful. You know, when that patient goes home and their, you know, son who wants to understand what happened has some questions, that AI should be available to continue that conversation. And the way you can improve that experience and streamline things and, you know, involve the people who advise you. I don’t understand why that’s not more adopted, because there you still have the human in the loop making that final decision.  But even for, like, follow-up calls to make sure the patient did things, to understand if they have concerns and knowing when to escalate back to the doctor, the benefit is incredible. And, you know, that thing is ready for prime time. That paradigm is ready for prime time, in my view.  LEE: Yeah, there are some good products, but it seems like the number one use right now—and we kind of got this from some of the previous guests in previous episodes—is the use of AI just to respond to emails from patients.Does that make sense to you?  BUBECK: Yeah. So maybe I want to second what Bill was saying but maybe take a step back first. You know, two years ago, like, the concept of clinical scribes, which is one of the things that we’re talking about right now, it would have sounded, in fact, it sounded two years ago, borderline dangerous. Because everybody was worried about hallucinations. What happened if you have this AI listening in and then it transcribes, you know, something wrong?  Now, two years later, I think it’s mostly working. And in fact, it is not yet, you know, fully adopted. You’re right. But it is in production. It is used, you know, in many, many places. So this rate of progress is astounding because it wasn’t obvious that we would be able to overcome those obstacles of hallucination. It’s not to say that hallucinations are fully solved. In the case of the closed system, they are.   Now, I think more generally what’s going on in the background is that there is something that we, that certainly I, underestimated, which is this management overhead. So I think the reason why this is not adopted everywhere is really a training and teaching aspect. People need to be taught, like, those systems, how to interact with them.  And one example that I really like, a study that recently appeared where they tried to use ChatGPT for diagnosis and they were comparing doctors without and with ChatGPT. And the amazing thing … so this was a set of cases where the accuracy of the doctors alone was around 75%. ChatGPT alone was 90%. So that’s already kind of mind blowing. But then the kicker is that doctors with ChatGPT was 80%.   Intelligence alone is not enough. It’s also how it’s presented, how you interact with it. And ChatGPT, it’s an amazing tool. Obviously, I absolutely love it. But it’s not … you don’t want a doctor to have to type in, you know, prompts and use it that way.  It should be, as Bill was saying, kind of running continuously in the background, sending you notifications. And you have to be really careful of the rate at which those notifications are being sent. Because if they are too frequent, then the doctor will learn to ignore them. So you have to … all of those things matter, in fact, at least as much as the level of intelligence of the machine.  LEE: One of the things I think about, Bill, in that scenario that you described, doctors do some thinking about the patient when they write the note. So, you know, I’m always a little uncertain whether it’s actually … you know, you wouldn’t necessarily want to fully automate this, I don’t think. Or at least there needs to be some prompt to the doctor to make sure that the doctor puts some thought into what happened in the encounter with the patient. Does that make sense to you at all?  GATES: At this stage, you know, I’d still put the onus on the doctor to write the conclusions and the summary and not delegate that.  The tradeoffs you make a little bit are somewhat dependent on the situation you’re in. If you’re in Africa, So, yes, the doctor’s still going to have to do a lot of work, but just the quality of letting the patient and the people around them interact and ask questions and have things explained, that alone is such a quality improvement. It’s mind blowing.   LEE: So since you mentioned, you know, Africa—and, of course, this touches on the mission and some of the priorities of the Gates Foundation and this idea of democratization of access to expert medical care—what’s the most interesting stuff going on right now? Are there people and organizations or technologies that are impressing you or that you’re tracking?  GATES: Yeah. So the Gates Foundation has given out a lot of grants to people in Africa doing education, agriculture but more healthcare examples than anything. And the way these things start off, they often start out either being patient-centric in a narrow situation, like, OK, I’m a pregnant woman; talk to me. Or, I have infectious disease symptoms; talk to me. Or they’re connected to a health worker where they’re helping that worker get their job done. And we have lots of pilots out, you know, in both of those cases.   The dream would be eventually to have the thing the patient consults be so broad that it’s like having a doctor available who understands the local things.   LEE: Right.   GATES: We’re not there yet. But over the next two or three years, you know, particularly given the worsening financial constraints against African health systems, where the withdrawal of money has been dramatic, you know, figuring out how to take this—what I sometimes call “free intelligence”—and build a quality health system around that, we will have to be more radical in low-income countries than any rich country is ever going to be.   LEE: Also, there’s maybe a different regulatory environment, so some of those things maybe are easier? Because right now, I think the world hasn’t figured out how to and whether to regulate, let’s say, an AI that might give a medical diagnosis or write a prescription for a medication.  BUBECK: Yeah. I think one issue with this, and it’s also slowing down the deployment of AI in healthcare more generally, is a lack of proper benchmark. Because, you know, you were mentioning the USMLE, for example. That’s a great test to test human beings and their knowledge of healthcare and medicine. But it’s not a great test to give to an AI.  It’s not asking the right questions. So finding what are the right questions to test whether an AI system is ready to give diagnosis in a constrained setting, that’s a very, very important direction, which to my surprise, is not yet accelerating at the rate that I was hoping for.  LEE: OK, so that gives me an excuse to get more now into the core AI tech because something I’ve discussed with both of you is this issue of what are the right tests. And you both know the very first test I give to any new spin of an LLM is I present a patient, the results—a mythical patient—the results of my physical exam, my mythical physical exam. Maybe some results of some initial labs. And then I present or propose a differential diagnosis. And if you’re not in medicine, a differential diagnosis you can just think of as a prioritized list of the possible diagnoses that fit with all that data. And in that proposed differential, I always intentionally make two mistakes.  I make a textbook technical error in one of the possible elements of the differential diagnosis, and I have an error of omission. And, you know, I just want to know, does the LLM understand what I’m talking about? And all the good ones out there do now. But then I want to know, can it spot the errors? And then most importantly, is it willing to tell me I’m wrong, that I’ve made a mistake?   That last piece seems really hard for AI today. And so let me ask you first, Seb, because at the time of this taping, of course, there was a new spin of GPT-4o last week that became overly sycophantic. In other words, it was actually prone in that test of mine not only to not tell me I’m wrong, but it actually praised me for the creativity of my differential.What’s up with that?  BUBECK: Yeah, I guess it’s a testament to the fact that training those models is still more of an art than a science. So it’s a difficult job. Just to be clear with the audience, we have rolled back thatversion of GPT-4o, so now we don’t have the sycophant version out there.  Yeah, no, it’s a really difficult question. It has to do … as you said, it’s very technical. It has to do with the post-training and how, like, where do you nudge the model? So, you know, there is this very classical by now technique called RLHF, where you push the model in the direction of a certain reward model. So the reward model is just telling the model, you know, what behavior is good, what behavior is bad.  But this reward model is itself an LLM, and, you know, Bill was saying at the very beginning of the conversation that we don’t really understand how those LLMs deal with concepts like, you know, where is the capital of France located? Things like that. It is the same thing for this reward model. We don’t know why it says that it prefers one output to another, and whether this is correlated with some sycophancy is, you know, something that we discovered basically just now. That if you push too hard in optimization on this reward model, you will get a sycophant model.  So it’s kind of … what I’m trying to say is we became too good at what we were doing, and we ended up, in fact, in a trap of the reward model.  LEE: I mean, you do want … it’s a difficult balance because you do want models to follow your desires and …  BUBECK: It’s a very difficult, very difficult balance.  LEE: So this brings up then the following question for me, which is the extent to which we think we’ll need to have specially trained models for things. So let me start with you, Bill. Do you have a point of view on whether we will need to, you know, quote-unquote take AI models to med school? Have them specially trained? Like, if you were going to deploy something to give medical care in underserved parts of the world, do we need to do something special to create those models?  GATES: We certainly need to teach them the African languages and the unique dialects so that the multimedia interactions are very high quality. We certainly need to teach them the disease prevalence and unique disease patterns like, you know, neglected tropical diseases and malaria. So we need to gather a set of facts that somebody trying to go for a US customer base, you know, wouldn’t necessarily have that in there.  Those two things are actually very straightforward because the additional training time is small. I’d say for the next few years, we’ll also need to do reinforcement learning about the context of being a doctor and how important certain behaviors are. Humans learn over the course of their life to some degree that, I’m in a different context and the way I behave in terms of being willing to criticize or be nice, you know, how important is it? Who’s here? What’s my relationship to them?   Right now, these machines don’t have that broad social experience. And so if you know it’s going to be used for health things, a lot of reinforcement learning of the very best humans in that context would still be valuable. Eventually, the models will, having read all the literature of the world about good doctors, bad doctors, it’ll understand as soon as you say, “I want you to be a doctor diagnosing somebody.” All of the implicit reinforcement that fits that situation, you know, will be there. LEE: Yeah. GATES: And so I hope three years from now, we don’t have to do that reinforcement learning. But today, for any medical context, you would want a lot of data to reinforce tone, willingness to say things when, you know, there might be something significant at stake.  LEE: Yeah. So, you know, something Bill said, kind of, reminds me of another thing that I think we missed, which is, the context also … and the specialization also pertains to different, I guess, what we still call “modes,” although I don’t know if the idea of multimodal is the same as it was two years ago. But, you know, what do you make of all of the hubbub around—in fact, within Microsoft Research, this is a big deal, but I think we’re far from alone—you know, medical images and vision, video, proteins and molecules, cell, you know, cellular data and so on.  BUBECK: Yeah. OK. So there is a lot to say to everything … to the last, you know, couple of minutes. Maybe on the specialization aspect, you know, I think there is, hiding behind this, a really fundamental scientific question of whether eventually we have a singular AGIthat kind of knows everything and you can just put, you know, explain your own context and it will just get it and understand everything.  That’s one vision. I have to say, I don’t particularly believe in this vision. In fact, we humans are not like that at all. I think, hopefully, we are general intelligences, yet we have to specialize a lot. And, you know, I did myself a lot of RL, reinforcement learning, on mathematics. Like, that’s what I did, you know, spent a lot of time doing that. And I didn’t improve on other aspects. You know, in fact, I probably degraded in other aspects.So it’s … I think it’s an important example to have in mind.  LEE: I think I might disagree with you on that, though, because, like, doesn’t a model have to see both good science and bad science in order to be able to gain the ability to discern between the two?  BUBECK: Yeah, no, that absolutely. I think there is value in seeing the generality, in having a very broad base. But then you, kind of, specialize on verticals. And this is where also, you know, open-weights model, which we haven’t talked about yet, are really important because they allow you to provide this broad base to everyone. And then you can specialize on top of it.  LEE: So we have about three hours of stuff to talk about, but our time is actually running low. BUBECK: Yes, yes, yes.   LEE: So I think I want … there’s a more provocative question. It’s almost a silly question, but I need to ask it of the two of you, which is, is there a future, you know, where AI replaces doctors or replaces, you know, medical specialties that we have today? So what does the world look like, say, five years from now?  GATES: Well, it’s important to distinguish healthcare discovery activity from healthcare delivery activity. We focused mostly on delivery. I think it’s very much within the realm of possibility that the AI is not only accelerating healthcare discovery but substituting for a lot of the roles of, you know, I’m an organic chemist, or I run various types of assays. I can see those, which are, you know, testable-output-type jobs but with still very high value, I can see, you know, some replacement in those areas before the doctor.   The doctor, still understanding the human condition and long-term dialogues, you know, they’ve had a lifetime of reinforcement of that, particularly when you get into areas like mental health. So I wouldn’t say in five years, either people will choose to adopt it, but it will be profound that there’ll be this nearly free intelligence that can do follow-up, that can help you, you know, make sure you went through different possibilities.  And so I’d say, yes, we’ll have doctors, but I’d say healthcare will be massively transformed in its quality and in efficiency by AI in that time period.  LEE: Is there a comparison, useful comparison, say, between doctors and, say, programmers, computer programmers, or doctors and, I don’t know, lawyers?  GATES: Programming is another one that has, kind of, a mathematical correctness to it, you know, and so the objective function that you’re trying to reinforce to, as soon as you can understand the state machines, you can have something that’s “checkable”; that’s correct. So I think programming, you know, which is weird to say, that the machine will beat us at most programming tasks before we let it take over roles that have deep empathy, you know, physical presence and social understanding in them.  LEE: Yeah. By the way, you know, I fully expect in five years that AI will produce mathematical proofs that are checkable for validity, easily checkable, because they’ll be written in a proof-checking language like Lean or something but will be so complex that no human mathematician can understand them. I expect that to happen.   I can imagine in some fields, like cellular biology, we could have the same situation in the future because the molecular pathways, the chemistry, biochemistry of human cells or living cells is as complex as any mathematics, and so it seems possible that we may be in a state where in wet lab, we see, Oh yeah, this actually works, but no one can understand why.  BUBECK: Yeah, absolutely. I mean, I think I really agree with Bill’s distinction of the discovery and the delivery, and indeed, the discovery’s when you can check things, and at the end, there is an artifact that you can verify. You know, you can run the protocol in the wet lab and seeproduced what you wanted. So I absolutely agree with that.   And in fact, you know, we don’t have to talk five years from now. I don’t know if you know, but just recently, there was a paper that was published on a scientific discovery using o3- mini. So this is really amazing. And, you know, just very quickly, just so people know, it was about this statistical physics model, the frustrated Potts model, which has to do with coloring, and basically, the case of three colors, like, more than two colors was open for a long time, and o3 was able to reduce the case of three colors to two colors.   LEE: Yeah.  BUBECK: Which is just, like, astounding. And this is not … this is now. This is happening right now. So this is something that I personally didn’t expect it would happen so quickly, and it’s due to those reasoning models.   Now, on the delivery side, I would add something more to it for the reason why doctors and, in fact, lawyers and coders will remain for a long time, and it’s because we still don’t understand how those models generalize. Like, at the end of the day, we are not able to tell you when they are confronted with a really new, novel situation, whether they will work or not.  Nobody is able to give you that guarantee. And I think until we understand this generalization better, we’re not going to be willing to just let the system in the wild without human supervision.  LEE: But don’t human doctors, human specialists … so, for example, a cardiologist sees a patient in a certain way that a nephrologist …  BUBECK: Yeah. LEE: … or an endocrinologist might not. BUBECK: That’s right. But another cardiologist will understand and, kind of, expect a certain level of generalization from their peer. And this, we just don’t have it with AI models. Now, of course, you’re exactly right. That generalization is also hard for humans. Like, if you have a human trained for one task and you put them into another task, then you don’t … you often don’t know. LEE: OK. You know, the podcast is focused on what’s happened over the last two years. But now, I’d like one provocative prediction about what you think the world of AI and medicine is going to be at some point in the future. You pick your timeframe. I don’t care if it’s two years or 20 years from now, but, you know, what do you think will be different about AI in medicine in that future than today?  BUBECK: Yeah, I think the deployment is going to accelerate soon. Like, we’re really not missing very much. There is this enormous capability overhang. Like, even if progress completely stopped, with current systems, we can do a lot more than what we’re doing right now. So I think this will … this has to be realized, you know, sooner rather than later.  And I think it’s probably dependent on these benchmarks and proper evaluation and tying this with regulation. So these are things that take time in human society and for good reason. But now we already are at two years; you know, give it another two years and it should be really …   LEE: Will AI prescribe your medicines? Write your prescriptions?  BUBECK: I think yes. I think yes.  LEE: OK. Bill?  GATES: Well, I think the next two years, we’ll have massive pilots, and so the amount of use of the AI, still in a copilot-type mode, you know, we should get millions of patient visits, you know, both in general medicine and in the mental health side, as well. And I think that’s going to build up both the data and the confidence to give the AI some additional autonomy. You know, are you going to let it talk to you at night when you’re panicked about your mental health with some ability to escalate? And, you know, I’ve gone so far as to tell politicians with national health systems that if they deploy AI appropriately, that the quality of care, the overload of the doctors, the improvement in the economics will be enough that their voters will be stunned because they just don’t expect this, and, you know, they could be reelectedjust on this one thing of fixing what is a very overloaded and economically challenged health system in these rich countries.  You know, my personal role is going to be to make sure that in the poorer countries, there isn’t some lag; in fact, in many cases, that we’ll be more aggressive because, you know, we’re comparing to having no access to doctors at all. And, you know, so I think whether it’s India or Africa, there’ll be lessons that are globally valuable because we need medical intelligence. And, you know, thank god AI is going to provide a lot of that.  LEE: Well, on that optimistic note, I think that’s a good way to end. Bill, Seb, really appreciate all of this.   I think the most fundamental prediction we made in the book is that AI would actually find its way into the practice of medicine, and I think that that at least has come true, maybe in different ways than we expected, but it’s come true, and I think it’ll only accelerate from here. So thanks again, both of you.   GATES: Yeah. Thanks, you guys.  BUBECK: Thank you, Peter. Thanks, Bill.  LEE: I just always feel such a sense of privilege to have a chance to interact and actually work with people like Bill and Sébastien.    With Bill, I’m always amazed at how practically minded he is. He’s really thinking about the nuts and bolts of what AI might be able to do for people, and his thoughts about underserved parts of the world, the idea that we might actually be able to empower people with access to expert medical knowledge, I think is both inspiring and amazing.   And then, Seb, Sébastien Bubeck, he’s just absolutely a brilliant mind. He has a really firm grip on the deep mathematics of artificial intelligence and brings that to bear in his research and development work. And where that mathematics takes him isn’t just into the nuts and bolts of algorithms but into philosophical questions about the nature of intelligence.   One of the things that Sébastien brought up was the state of evaluation of AI systems. And indeed, he was fairly critical in our conversation. But of course, the world of AI research and development is just moving so fast, and indeed, since we recorded our conversation, OpenAI, in fact, released a new evaluation metric that is directly relevant to medical applications, and that is something called HealthBench. And Microsoft Research also released a new evaluation approach or process called ADeLe.   HealthBench and ADeLe are examples of new approaches to evaluating AI models that are less about testing their knowledge and ability to pass multiple-choice exams and instead are evaluation approaches designed to assess how well AI models are able to complete tasks that actually arise every day in typical healthcare or biomedical research settings. These are examples of really important good work that speak to how well AI models work in the real world of healthcare and biomedical research and how well they can collaborate with human beings in those settings.  You know, I asked Bill and Seb to make some predictions about the future. You know, my own answer, I expect that we’re going to be able to use AI to change how we diagnose patients, change how we decide treatment options.   If you’re a doctor or a nurse and you encounter a patient, you’ll ask questions, do a physical exam, you know, call out for labs just like you do today, but then you’ll be able to engage with AI based on all of that data and just ask, you know, based on all the other people who have gone through the same experience, who have similar data, how were they diagnosed? How were they treated? What were their outcomes? And what does that mean for the patient I have right now? Some people call it the “patients like me” paradigm. And I think that’s going to become real because of AI within our lifetimes. That idea of really grounding the delivery in healthcare and medical practice through data and intelligence, I actually now don’t see any barriers to that future becoming real.   I’d like to extend another big thank you to Bill and Sébastien for their time. And to our listeners, as always, it’s a pleasure to have you along for the ride. I hope you’ll join us for our remaining conversations, as well as a second coauthor roundtable with Carey and Zak.   Until next time.   #how #reshaping #future #healthcare #medical
    WWW.MICROSOFT.COM
    How AI is reshaping the future of healthcare and medical research
    Transcript [MUSIC]      [BOOK PASSAGE]   PETER LEE: “In ‘The Little Black Bag,’ a classic science fiction story, a high-tech doctor’s kit of the future is accidentally transported back to the 1950s, into the shaky hands of a washed-up, alcoholic doctor. The ultimate medical tool, it redeems the doctor wielding it, allowing him to practice gratifyingly heroic medicine. … The tale ends badly for the doctor and his treacherous assistant, but it offered a picture of how advanced technology could transform medicine—powerful when it was written nearly 75 years ago and still so today. What would be the Al equivalent of that little black bag? At this moment when new capabilities are emerging, how do we imagine them into medicine?”   [END OF BOOK PASSAGE]     [THEME MUSIC]     This is The AI Revolution in Medicine, Revisited. I’m your host, Peter Lee.    Shortly after OpenAI’s GPT-4 was publicly released, Carey Goldberg, Dr. Zak Kohane, and I published The AI Revolution in Medicine to help educate the world of healthcare and medical research about the transformative impact this new generative AI technology could have. But because we wrote the book when GPT-4 was still a secret, we had to speculate. Now, two years later, what did we get right, and what did we get wrong?     In this series, we’ll talk to clinicians, patients, hospital administrators, and others to understand the reality of AI in the field and where we go from here.   [THEME MUSIC FADES] The book passage I read at the top is from “Chapter 10: The Big Black Bag.”  In imagining AI in medicine, Carey, Zak, and I included in our book two fictional accounts. In the first, a medical resident consults GPT-4 on her personal phone as the patient in front of her crashes. Within seconds, it offers an alternate response based on recent literature. In the second account, a 90-year-old woman with several chronic conditions is living independently and receiving near-constant medical support from an AI aide.    In our conversations with the guests we’ve spoken to so far, we’ve caught a glimpse of these predicted futures, seeing how clinicians and patients are actually using AI today and how developers are leveraging the technology in the healthcare products and services they’re creating. In fact, that first fictional account isn’t so fictional after all, as most of the doctors in the real world actually appear to be using AI at least occasionally—and sometimes much more than occasionally—to help in their daily clinical work. And as for the second fictional account, which is more of a science fiction account, it seems we are indeed on the verge of a new way of delivering and receiving healthcare, though the future is still very much open.  As we continue to examine the current state of AI in healthcare and its potential to transform the field, I’m pleased to welcome Bill Gates and Sébastien Bubeck.   Bill may be best known as the co-founder of Microsoft, having created the company with his childhood friend Paul Allen in 1975. He’s now the founder of Breakthrough Energy, which aims to advance clean energy innovation, and TerraPower, a company developing groundbreaking nuclear energy and science technologies. He also chairs the world’s largest philanthropic organization, the Gates Foundation, and focuses on solving a variety of health challenges around the globe and here at home.  Sébastien is a research lead at OpenAI. He was previously a distinguished scientist, vice president of AI, and a colleague of mine here at Microsoft, where his work included spearheading the development of the family of small language models known as Phi. While at Microsoft, he also coauthored the discussion-provoking 2023 paper “Sparks of Artificial General Intelligence,” which presented the results of early experiments with GPT-4 conducted by a small team from Microsoft Research.    [TRANSITION MUSIC]   Here’s my conversation with Bill Gates and Sébastien Bubeck.  LEE: Bill, welcome.  BILL GATES: Thank you.  LEE: Seb …  SÉBASTIEN BUBECK: Yeah. Hi, hi, Peter. Nice to be here.  LEE: You know, one of the things that I’ve been doing just to get the conversation warmed up is to talk about origin stories, and what I mean about origin stories is, you know, what was the first contact that you had with large language models or the concept of generative AI that convinced you or made you think that something really important was happening?  And so, Bill, I think I’ve heard the story about, you know, the time when the OpenAI folks—Sam Altman, Greg Brockman, and others—showed you something, but could we hear from you what those early encounters were like and what was going through your mind?   GATES: Well, I’d been visiting OpenAI soon after it was created to see things like GPT-2 and to see the little arm they had that was trying to match human manipulation and, you know, looking at their games like Dota that they were trying to get as good as human play. And honestly, I didn’t think the language model stuff they were doing, even when they got to GPT-3, would show the ability to learn, you know, in the same sense that a human reads a biology book and is able to take that knowledge and access it not only to pass a test but also to create new medicines.  And so my challenge to them was that if their LLM could get a five on the advanced placement biology test, then I would say, OK, it took biologic knowledge and encoded it in an accessible way and that I didn’t expect them to do that very quickly but it would be profound.   And it was only about six months after I challenged them to do that, that an early version of GPT-4 they brought up to a dinner at my house, and in fact, it answered most of the questions that night very well. The one it got totally wrong, we were … because it was so good, we kept thinking, Oh, we must be wrong. It turned out it was a math weakness [LAUGHTER] that, you know, we later understood that that was an area of, weirdly, of incredible weakness of those early models. But, you know, that was when I realized, OK, the age of cheap intelligence was at its beginning.  LEE: Yeah. So I guess it seems like you had something similar to me in that my first encounters, I actually harbored some skepticism. Is it fair to say you were skeptical before that?  GATES: Well, the idea that we’ve figured out how to encode and access knowledge in this very deep sense without even understanding the nature of the encoding, …  LEE: Right.   GATES: … that is a bit weird.   LEE: Yeah.  GATES: We have an algorithm that creates the computation, but even say, OK, where is the president’s birthday stored in there? Where is this fact stored in there? The fact that even now when we’re playing around, getting a little bit more sense of it, it’s opaque to us what the semantic encoding is, it’s, kind of, amazing to me. I thought the invention of knowledge storage would be an explicit way of encoding knowledge, not an implicit statistical training.  LEE: Yeah, yeah. All right. So, Seb, you know, on this same topic, you know, I got—as we say at Microsoft—I got pulled into the tent. [LAUGHS]  BUBECK: Yes.   LEE: Because this was a very secret project. And then, um, I had the opportunity to select a small number of researchers in MSR [Microsoft Research] to join and start investigating this thing seriously. And the first person I pulled in was you.  BUBECK: Yeah.  LEE: And so what were your first encounters? Because I actually don’t remember what happened then.  BUBECK: Oh, I remember it very well. [LAUGHS] My first encounter with GPT-4 was in a meeting with the two of you, actually. But my kind of first contact, the first moment where I realized that something was happening with generative AI, was before that. And I agree with Bill that I also wasn’t too impressed by GPT-3.  I though that it was kind of, you know, very naturally mimicking the web, sort of parroting what was written there in a nice way. Still in a way which seemed very impressive. But it wasn’t really intelligent in any way. But shortly after GPT-3, there was a model before GPT-4 that really shocked me, and this was the first image generation model, DALL-E 1.  So that was in 2021. And I will forever remember the press release of OpenAI where they had this prompt of an avocado chair and then you had this image of the avocado chair. [LAUGHTER] And what really shocked me is that clearly the model kind of “understood” what is a chair, what is an avocado, and was able to merge those concepts.  So this was really, to me, the first moment where I saw some understanding in those models.   LEE: So this was, just to get the timing right, that was before I pulled you into the tent.  BUBECK: That was before. That was like a year before.  LEE: Right.   BUBECK: And now I will tell you how, you know, we went from that moment to the meeting with the two of you and GPT-4.  So once I saw this kind of understanding, I thought, OK, fine. It understands concept, but it’s still not able to reason. It cannot—as, you know, Bill was saying—it cannot learn from your document. It cannot reason.   So I set out to try to prove that. You know, this is what I was in the business of at the time, trying to prove things in mathematics. So I was trying to prove that basically autoregressive transformers could never reason. So I was trying to prove this. And after a year of work, I had something reasonable to show. And so I had the meeting with the two of you, and I had this example where I wanted to say, there is no way that an LLM is going to be able to do x.  And then as soon as I … I don’t know if you remember, Bill. But as soon as I said that, you said, oh, but wait a second. I had, you know, the OpenAI crew at my house recently, and they showed me a new model. Why don’t we ask this new model this question?   LEE: Yeah. BUBECK: And we did, and it solved it on the spot. And that really, honestly, just changed my life. Like, you know, I had been working for a year trying to say that this was impossible. And just right there, it was shown to be possible.   LEE: [LAUGHS] One of the very first things I got interested in—because I was really thinking a lot about healthcare—was healthcare and medicine.  And I don’t know if the two of you remember, but I ended up doing a lot of tests. I ran through, you know, step one and step two of the US Medical Licensing Exam. Did a whole bunch of other things. I wrote this big report. It was, you know, I can’t remember … a couple hundred pages.   And I needed to share this with someone. I didn’t … there weren’t too many people I could share it with. So I sent, I think, a copy to you, Bill. Sent a copy to you, Seb.   I hardly slept for about a week putting that report together. And, yeah, and I kept working on it. But I was far from alone. I think everyone who was in the tent, so to speak, in those early days was going through something pretty similar. All right. So I think … of course, a lot of what I put in the report also ended up being examples that made it into the book.  But the main purpose of this conversation isn’t to reminisce about [LAUGHS] or indulge in those reminiscences but to talk about what’s happening in healthcare and medicine. And, you know, as I said, we wrote this book. We did it very, very quickly. Seb, you helped. Bill, you know, you provided a review and some endorsements.  But, you know, honestly, we didn’t know what we were talking about because no one had access to this thing. And so we just made a bunch of guesses. So really, the whole thing I wanted to probe with the two of you is, now with two years of experience out in the world, what, you know, what do we think is happening today?  You know, is AI actually having an impact, positive or negative, on healthcare and medicine? And what do we now think is going to happen in the next two years, five years, or 10 years? And so I realize it’s a little bit too abstract to just ask it that way. So let me just try to narrow the discussion and guide us a little bit.   Um, the kind of administrative and clerical work, paperwork, around healthcare—and we made a lot of guesses about that—that appears to be going well, but, you know, Bill, I know we’ve discussed that sometimes that you think there ought to be a lot more going on. Do you have a viewpoint on how AI is actually finding its way into reducing paperwork?  GATES: Well, I’m stunned … I don’t think there should be a patient-doctor meeting where the AI is not sitting in and both transcribing, offering to help with the paperwork, and even making suggestions, although the doctor will be the one, you know, who makes the final decision about the diagnosis and whatever prescription gets done.   It’s so helpful. You know, when that patient goes home and their, you know, son who wants to understand what happened has some questions, that AI should be available to continue that conversation. And the way you can improve that experience and streamline things and, you know, involve the people who advise you. I don’t understand why that’s not more adopted, because there you still have the human in the loop making that final decision.  But even for, like, follow-up calls to make sure the patient did things, to understand if they have concerns and knowing when to escalate back to the doctor, the benefit is incredible. And, you know, that thing is ready for prime time. That paradigm is ready for prime time, in my view.  LEE: Yeah, there are some good products, but it seems like the number one use right now—and we kind of got this from some of the previous guests in previous episodes—is the use of AI just to respond to emails from patients. [LAUGHTER] Does that make sense to you?  BUBECK: Yeah. So maybe I want to second what Bill was saying but maybe take a step back first. You know, two years ago, like, the concept of clinical scribes, which is one of the things that we’re talking about right now, it would have sounded, in fact, it sounded two years ago, borderline dangerous. Because everybody was worried about hallucinations. What happened if you have this AI listening in and then it transcribes, you know, something wrong?  Now, two years later, I think it’s mostly working. And in fact, it is not yet, you know, fully adopted. You’re right. But it is in production. It is used, you know, in many, many places. So this rate of progress is astounding because it wasn’t obvious that we would be able to overcome those obstacles of hallucination. It’s not to say that hallucinations are fully solved. In the case of the closed system, they are.   Now, I think more generally what’s going on in the background is that there is something that we, that certainly I, underestimated, which is this management overhead. So I think the reason why this is not adopted everywhere is really a training and teaching aspect. People need to be taught, like, those systems, how to interact with them.  And one example that I really like, a study that recently appeared where they tried to use ChatGPT for diagnosis and they were comparing doctors without and with ChatGPT (opens in new tab). And the amazing thing … so this was a set of cases where the accuracy of the doctors alone was around 75%. ChatGPT alone was 90%. So that’s already kind of mind blowing. But then the kicker is that doctors with ChatGPT was 80%.   Intelligence alone is not enough. It’s also how it’s presented, how you interact with it. And ChatGPT, it’s an amazing tool. Obviously, I absolutely love it. But it’s not … you don’t want a doctor to have to type in, you know, prompts and use it that way.  It should be, as Bill was saying, kind of running continuously in the background, sending you notifications. And you have to be really careful of the rate at which those notifications are being sent. Because if they are too frequent, then the doctor will learn to ignore them. So you have to … all of those things matter, in fact, at least as much as the level of intelligence of the machine.  LEE: One of the things I think about, Bill, in that scenario that you described, doctors do some thinking about the patient when they write the note. So, you know, I’m always a little uncertain whether it’s actually … you know, you wouldn’t necessarily want to fully automate this, I don’t think. Or at least there needs to be some prompt to the doctor to make sure that the doctor puts some thought into what happened in the encounter with the patient. Does that make sense to you at all?  GATES: At this stage, you know, I’d still put the onus on the doctor to write the conclusions and the summary and not delegate that.  The tradeoffs you make a little bit are somewhat dependent on the situation you’re in. If you’re in Africa, So, yes, the doctor’s still going to have to do a lot of work, but just the quality of letting the patient and the people around them interact and ask questions and have things explained, that alone is such a quality improvement. It’s mind blowing.   LEE: So since you mentioned, you know, Africa—and, of course, this touches on the mission and some of the priorities of the Gates Foundation and this idea of democratization of access to expert medical care—what’s the most interesting stuff going on right now? Are there people and organizations or technologies that are impressing you or that you’re tracking?  GATES: Yeah. So the Gates Foundation has given out a lot of grants to people in Africa doing education, agriculture but more healthcare examples than anything. And the way these things start off, they often start out either being patient-centric in a narrow situation, like, OK, I’m a pregnant woman; talk to me. Or, I have infectious disease symptoms; talk to me. Or they’re connected to a health worker where they’re helping that worker get their job done. And we have lots of pilots out, you know, in both of those cases.   The dream would be eventually to have the thing the patient consults be so broad that it’s like having a doctor available who understands the local things.   LEE: Right.   GATES: We’re not there yet. But over the next two or three years, you know, particularly given the worsening financial constraints against African health systems, where the withdrawal of money has been dramatic, you know, figuring out how to take this—what I sometimes call “free intelligence”—and build a quality health system around that, we will have to be more radical in low-income countries than any rich country is ever going to be.   LEE: Also, there’s maybe a different regulatory environment, so some of those things maybe are easier? Because right now, I think the world hasn’t figured out how to and whether to regulate, let’s say, an AI that might give a medical diagnosis or write a prescription for a medication.  BUBECK: Yeah. I think one issue with this, and it’s also slowing down the deployment of AI in healthcare more generally, is a lack of proper benchmark. Because, you know, you were mentioning the USMLE [United States Medical Licensing Examination], for example. That’s a great test to test human beings and their knowledge of healthcare and medicine. But it’s not a great test to give to an AI.  It’s not asking the right questions. So finding what are the right questions to test whether an AI system is ready to give diagnosis in a constrained setting, that’s a very, very important direction, which to my surprise, is not yet accelerating at the rate that I was hoping for.  LEE: OK, so that gives me an excuse to get more now into the core AI tech because something I’ve discussed with both of you is this issue of what are the right tests. And you both know the very first test I give to any new spin of an LLM is I present a patient, the results—a mythical patient—the results of my physical exam, my mythical physical exam. Maybe some results of some initial labs. And then I present or propose a differential diagnosis. And if you’re not in medicine, a differential diagnosis you can just think of as a prioritized list of the possible diagnoses that fit with all that data. And in that proposed differential, I always intentionally make two mistakes.  I make a textbook technical error in one of the possible elements of the differential diagnosis, and I have an error of omission. And, you know, I just want to know, does the LLM understand what I’m talking about? And all the good ones out there do now. But then I want to know, can it spot the errors? And then most importantly, is it willing to tell me I’m wrong, that I’ve made a mistake?   That last piece seems really hard for AI today. And so let me ask you first, Seb, because at the time of this taping, of course, there was a new spin of GPT-4o last week that became overly sycophantic. In other words, it was actually prone in that test of mine not only to not tell me I’m wrong, but it actually praised me for the creativity of my differential. [LAUGHTER] What’s up with that?  BUBECK: Yeah, I guess it’s a testament to the fact that training those models is still more of an art than a science. So it’s a difficult job. Just to be clear with the audience, we have rolled back that [LAUGHS] version of GPT-4o, so now we don’t have the sycophant version out there.  Yeah, no, it’s a really difficult question. It has to do … as you said, it’s very technical. It has to do with the post-training and how, like, where do you nudge the model? So, you know, there is this very classical by now technique called RLHF [reinforcement learning from human feedback], where you push the model in the direction of a certain reward model. So the reward model is just telling the model, you know, what behavior is good, what behavior is bad.  But this reward model is itself an LLM, and, you know, Bill was saying at the very beginning of the conversation that we don’t really understand how those LLMs deal with concepts like, you know, where is the capital of France located? Things like that. It is the same thing for this reward model. We don’t know why it says that it prefers one output to another, and whether this is correlated with some sycophancy is, you know, something that we discovered basically just now. That if you push too hard in optimization on this reward model, you will get a sycophant model.  So it’s kind of … what I’m trying to say is we became too good at what we were doing, and we ended up, in fact, in a trap of the reward model.  LEE: I mean, you do want … it’s a difficult balance because you do want models to follow your desires and …  BUBECK: It’s a very difficult, very difficult balance.  LEE: So this brings up then the following question for me, which is the extent to which we think we’ll need to have specially trained models for things. So let me start with you, Bill. Do you have a point of view on whether we will need to, you know, quote-unquote take AI models to med school? Have them specially trained? Like, if you were going to deploy something to give medical care in underserved parts of the world, do we need to do something special to create those models?  GATES: We certainly need to teach them the African languages and the unique dialects so that the multimedia interactions are very high quality. We certainly need to teach them the disease prevalence and unique disease patterns like, you know, neglected tropical diseases and malaria. So we need to gather a set of facts that somebody trying to go for a US customer base, you know, wouldn’t necessarily have that in there.  Those two things are actually very straightforward because the additional training time is small. I’d say for the next few years, we’ll also need to do reinforcement learning about the context of being a doctor and how important certain behaviors are. Humans learn over the course of their life to some degree that, I’m in a different context and the way I behave in terms of being willing to criticize or be nice, you know, how important is it? Who’s here? What’s my relationship to them?   Right now, these machines don’t have that broad social experience. And so if you know it’s going to be used for health things, a lot of reinforcement learning of the very best humans in that context would still be valuable. Eventually, the models will, having read all the literature of the world about good doctors, bad doctors, it’ll understand as soon as you say, “I want you to be a doctor diagnosing somebody.” All of the implicit reinforcement that fits that situation, you know, will be there. LEE: Yeah. GATES: And so I hope three years from now, we don’t have to do that reinforcement learning. But today, for any medical context, you would want a lot of data to reinforce tone, willingness to say things when, you know, there might be something significant at stake.  LEE: Yeah. So, you know, something Bill said, kind of, reminds me of another thing that I think we missed, which is, the context also … and the specialization also pertains to different, I guess, what we still call “modes,” although I don’t know if the idea of multimodal is the same as it was two years ago. But, you know, what do you make of all of the hubbub around—in fact, within Microsoft Research, this is a big deal, but I think we’re far from alone—you know, medical images and vision, video, proteins and molecules, cell, you know, cellular data and so on.  BUBECK: Yeah. OK. So there is a lot to say to everything … to the last, you know, couple of minutes. Maybe on the specialization aspect, you know, I think there is, hiding behind this, a really fundamental scientific question of whether eventually we have a singular AGI [artificial general intelligence] that kind of knows everything and you can just put, you know, explain your own context and it will just get it and understand everything.  That’s one vision. I have to say, I don’t particularly believe in this vision. In fact, we humans are not like that at all. I think, hopefully, we are general intelligences, yet we have to specialize a lot. And, you know, I did myself a lot of RL, reinforcement learning, on mathematics. Like, that’s what I did, you know, spent a lot of time doing that. And I didn’t improve on other aspects. You know, in fact, I probably degraded in other aspects. [LAUGHTER] So it’s … I think it’s an important example to have in mind.  LEE: I think I might disagree with you on that, though, because, like, doesn’t a model have to see both good science and bad science in order to be able to gain the ability to discern between the two?  BUBECK: Yeah, no, that absolutely. I think there is value in seeing the generality, in having a very broad base. But then you, kind of, specialize on verticals. And this is where also, you know, open-weights model, which we haven’t talked about yet, are really important because they allow you to provide this broad base to everyone. And then you can specialize on top of it.  LEE: So we have about three hours of stuff to talk about, but our time is actually running low. BUBECK: Yes, yes, yes.   LEE: So I think I want … there’s a more provocative question. It’s almost a silly question, but I need to ask it of the two of you, which is, is there a future, you know, where AI replaces doctors or replaces, you know, medical specialties that we have today? So what does the world look like, say, five years from now?  GATES: Well, it’s important to distinguish healthcare discovery activity from healthcare delivery activity. We focused mostly on delivery. I think it’s very much within the realm of possibility that the AI is not only accelerating healthcare discovery but substituting for a lot of the roles of, you know, I’m an organic chemist, or I run various types of assays. I can see those, which are, you know, testable-output-type jobs but with still very high value, I can see, you know, some replacement in those areas before the doctor.   The doctor, still understanding the human condition and long-term dialogues, you know, they’ve had a lifetime of reinforcement of that, particularly when you get into areas like mental health. So I wouldn’t say in five years, either people will choose to adopt it, but it will be profound that there’ll be this nearly free intelligence that can do follow-up, that can help you, you know, make sure you went through different possibilities.  And so I’d say, yes, we’ll have doctors, but I’d say healthcare will be massively transformed in its quality and in efficiency by AI in that time period.  LEE: Is there a comparison, useful comparison, say, between doctors and, say, programmers, computer programmers, or doctors and, I don’t know, lawyers?  GATES: Programming is another one that has, kind of, a mathematical correctness to it, you know, and so the objective function that you’re trying to reinforce to, as soon as you can understand the state machines, you can have something that’s “checkable”; that’s correct. So I think programming, you know, which is weird to say, that the machine will beat us at most programming tasks before we let it take over roles that have deep empathy, you know, physical presence and social understanding in them.  LEE: Yeah. By the way, you know, I fully expect in five years that AI will produce mathematical proofs that are checkable for validity, easily checkable, because they’ll be written in a proof-checking language like Lean or something but will be so complex that no human mathematician can understand them. I expect that to happen.   I can imagine in some fields, like cellular biology, we could have the same situation in the future because the molecular pathways, the chemistry, biochemistry of human cells or living cells is as complex as any mathematics, and so it seems possible that we may be in a state where in wet lab, we see, Oh yeah, this actually works, but no one can understand why.  BUBECK: Yeah, absolutely. I mean, I think I really agree with Bill’s distinction of the discovery and the delivery, and indeed, the discovery’s when you can check things, and at the end, there is an artifact that you can verify. You know, you can run the protocol in the wet lab and see [if you have] produced what you wanted. So I absolutely agree with that.   And in fact, you know, we don’t have to talk five years from now. I don’t know if you know, but just recently, there was a paper that was published on a scientific discovery using o3- mini (opens in new tab). So this is really amazing. And, you know, just very quickly, just so people know, it was about this statistical physics model, the frustrated Potts model, which has to do with coloring, and basically, the case of three colors, like, more than two colors was open for a long time, and o3 was able to reduce the case of three colors to two colors.   LEE: Yeah.  BUBECK: Which is just, like, astounding. And this is not … this is now. This is happening right now. So this is something that I personally didn’t expect it would happen so quickly, and it’s due to those reasoning models.   Now, on the delivery side, I would add something more to it for the reason why doctors and, in fact, lawyers and coders will remain for a long time, and it’s because we still don’t understand how those models generalize. Like, at the end of the day, we are not able to tell you when they are confronted with a really new, novel situation, whether they will work or not.  Nobody is able to give you that guarantee. And I think until we understand this generalization better, we’re not going to be willing to just let the system in the wild without human supervision.  LEE: But don’t human doctors, human specialists … so, for example, a cardiologist sees a patient in a certain way that a nephrologist …  BUBECK: Yeah. LEE: … or an endocrinologist might not. BUBECK: That’s right. But another cardiologist will understand and, kind of, expect a certain level of generalization from their peer. And this, we just don’t have it with AI models. Now, of course, you’re exactly right. That generalization is also hard for humans. Like, if you have a human trained for one task and you put them into another task, then you don’t … you often don’t know. LEE: OK. You know, the podcast is focused on what’s happened over the last two years. But now, I’d like one provocative prediction about what you think the world of AI and medicine is going to be at some point in the future. You pick your timeframe. I don’t care if it’s two years or 20 years from now, but, you know, what do you think will be different about AI in medicine in that future than today?  BUBECK: Yeah, I think the deployment is going to accelerate soon. Like, we’re really not missing very much. There is this enormous capability overhang. Like, even if progress completely stopped, with current systems, we can do a lot more than what we’re doing right now. So I think this will … this has to be realized, you know, sooner rather than later.  And I think it’s probably dependent on these benchmarks and proper evaluation and tying this with regulation. So these are things that take time in human society and for good reason. But now we already are at two years; you know, give it another two years and it should be really …   LEE: Will AI prescribe your medicines? Write your prescriptions?  BUBECK: I think yes. I think yes.  LEE: OK. Bill?  GATES: Well, I think the next two years, we’ll have massive pilots, and so the amount of use of the AI, still in a copilot-type mode, you know, we should get millions of patient visits, you know, both in general medicine and in the mental health side, as well. And I think that’s going to build up both the data and the confidence to give the AI some additional autonomy. You know, are you going to let it talk to you at night when you’re panicked about your mental health with some ability to escalate? And, you know, I’ve gone so far as to tell politicians with national health systems that if they deploy AI appropriately, that the quality of care, the overload of the doctors, the improvement in the economics will be enough that their voters will be stunned because they just don’t expect this, and, you know, they could be reelected [LAUGHTER] just on this one thing of fixing what is a very overloaded and economically challenged health system in these rich countries.  You know, my personal role is going to be to make sure that in the poorer countries, there isn’t some lag; in fact, in many cases, that we’ll be more aggressive because, you know, we’re comparing to having no access to doctors at all. And, you know, so I think whether it’s India or Africa, there’ll be lessons that are globally valuable because we need medical intelligence. And, you know, thank god AI is going to provide a lot of that.  LEE: Well, on that optimistic note, I think that’s a good way to end. Bill, Seb, really appreciate all of this.   I think the most fundamental prediction we made in the book is that AI would actually find its way into the practice of medicine, and I think that that at least has come true, maybe in different ways than we expected, but it’s come true, and I think it’ll only accelerate from here. So thanks again, both of you.  [TRANSITION MUSIC]  GATES: Yeah. Thanks, you guys.  BUBECK: Thank you, Peter. Thanks, Bill.  LEE: I just always feel such a sense of privilege to have a chance to interact and actually work with people like Bill and Sébastien.    With Bill, I’m always amazed at how practically minded he is. He’s really thinking about the nuts and bolts of what AI might be able to do for people, and his thoughts about underserved parts of the world, the idea that we might actually be able to empower people with access to expert medical knowledge, I think is both inspiring and amazing.   And then, Seb, Sébastien Bubeck, he’s just absolutely a brilliant mind. He has a really firm grip on the deep mathematics of artificial intelligence and brings that to bear in his research and development work. And where that mathematics takes him isn’t just into the nuts and bolts of algorithms but into philosophical questions about the nature of intelligence.   One of the things that Sébastien brought up was the state of evaluation of AI systems. And indeed, he was fairly critical in our conversation. But of course, the world of AI research and development is just moving so fast, and indeed, since we recorded our conversation, OpenAI, in fact, released a new evaluation metric that is directly relevant to medical applications, and that is something called HealthBench. And Microsoft Research also released a new evaluation approach or process called ADeLe.   HealthBench and ADeLe are examples of new approaches to evaluating AI models that are less about testing their knowledge and ability to pass multiple-choice exams and instead are evaluation approaches designed to assess how well AI models are able to complete tasks that actually arise every day in typical healthcare or biomedical research settings. These are examples of really important good work that speak to how well AI models work in the real world of healthcare and biomedical research and how well they can collaborate with human beings in those settings.  You know, I asked Bill and Seb to make some predictions about the future. You know, my own answer, I expect that we’re going to be able to use AI to change how we diagnose patients, change how we decide treatment options.   If you’re a doctor or a nurse and you encounter a patient, you’ll ask questions, do a physical exam, you know, call out for labs just like you do today, but then you’ll be able to engage with AI based on all of that data and just ask, you know, based on all the other people who have gone through the same experience, who have similar data, how were they diagnosed? How were they treated? What were their outcomes? And what does that mean for the patient I have right now? Some people call it the “patients like me” paradigm. And I think that’s going to become real because of AI within our lifetimes. That idea of really grounding the delivery in healthcare and medical practice through data and intelligence, I actually now don’t see any barriers to that future becoming real.  [THEME MUSIC]  I’d like to extend another big thank you to Bill and Sébastien for their time. And to our listeners, as always, it’s a pleasure to have you along for the ride. I hope you’ll join us for our remaining conversations, as well as a second coauthor roundtable with Carey and Zak.   Until next time.   [MUSIC FADES]
    0 Σχόλια 0 Μοιράστηκε
  • Will Gamble Architects restores and extends Hertfordshire farmhouse

    The farmhouse, Flint Farm, in North Hertfordshire, was in poor condition with a number of unsympathetic additions that had altered its character over the years.
    Will Gamble Architects was appointed to restore and extend it for a young couple who wanted to transform it into their long-term family home and improve the house’s relationship with its garden and wider farmyard setting.
    While the original brief had been to replace an existing conservatory with a new extension, the practice encouraged the client to extend by integrating an adjacent barn into the envelope of the reworked house, changing the way the property was used.Advertisement

    Existing unsympathetic extensions were removed and the internal layout was reconfigured, with a new linking element added between the barn and farmhouse.
    The series of internal spaces that has been created is designed to retain the character of the historic listed property.
    Architect’s view
    The barn was sensitively restored and converted into an informal living space. Its timber-framed structure was refurbished and left exposed to celebrate the historic fabric of the barn and the craftsmanship of its original construction. A contemporary picture window with parts of the historic timber frame exposed within its reveals frames a view of the garden, as well as the barn’s unique structure.
    The extension, that links both barn and farmhouse, is deliberately contemporary in appearance to ensure that the historic buildings remain legible. It’s low-rise, built into the sloping garden and particularly lightweight in appearance. Floor-to-ceiling glass sits on a plinth of semi-knapped flint, rooting the intervention into the garden. A ribbon of black steel, with shallow peaks and troughs hovers above. The form of this ribbon draws inspiration from the distinctive black timber-clad gables that characterise the farmhouse and the surrounding outbuildings of the old farmstead.
    Internally the addition’s structure is exposed, much like the historic timber framed structure of the farmhouse and the barn. The interiors are tactile, defined by texture and pattern and inspired by the characteristics of the old farmstead.
    Miles Kelsey, associate, Will Gamble ArchitectsAdvertisement

    Client’s view
    We bought the farmhouse as a family home to move out of our two-bed flat in north London.
    Will visited the farmhouse with us whilst we were working through the purchase to understand what we were looking to do and went on to support us through each stage.
    The farmhouse was a combination of the original 16th century timber-framed building that had been added to with unattractive, unusable, and poorly planned extensions that meant the house was completely disconnected from the garden.
    Will and Miles transformed the whole house including moving the front door, converting an adjacent barn and building the modern extension as our kitchen and dining room that makes the best of the garden and views.
    The process that Will and Miles ran was a perfect balance of what we wanted, Sophie’s specific tastes and creativity combined with the benefit of the architects views and what they have done before.
    What really stood out to us was the way they worked with the council during the planning process so we got consent for almost everything we wanted, expressing their own views but ensuring we were always leading the process and the attention to detail during the build stage.
    Overall we are incredibly happy with what Will and Miles helped us create and the way they led us through the whole process.

      Source:Will Gamble Architects

    Project data
    Location North Hertfordshire
    Start on site April 2023
    Completion February 2025
    Gross internal floor area 320m2
    Form of contract or procurement route JCT MW Building Contract. Design-Bid-Build
    Architect Will Gamble Architects
    Client Private
    Structural engineer Axiom Structures
    Principal designer Will Gamble Architects
    Main contractor Elite Construction
    #will #gamble #architects #restores #extends
    Will Gamble Architects restores and extends Hertfordshire farmhouse
    The farmhouse, Flint Farm, in North Hertfordshire, was in poor condition with a number of unsympathetic additions that had altered its character over the years. Will Gamble Architects was appointed to restore and extend it for a young couple who wanted to transform it into their long-term family home and improve the house’s relationship with its garden and wider farmyard setting. While the original brief had been to replace an existing conservatory with a new extension, the practice encouraged the client to extend by integrating an adjacent barn into the envelope of the reworked house, changing the way the property was used.Advertisement Existing unsympathetic extensions were removed and the internal layout was reconfigured, with a new linking element added between the barn and farmhouse. The series of internal spaces that has been created is designed to retain the character of the historic listed property. Architect’s view The barn was sensitively restored and converted into an informal living space. Its timber-framed structure was refurbished and left exposed to celebrate the historic fabric of the barn and the craftsmanship of its original construction. A contemporary picture window with parts of the historic timber frame exposed within its reveals frames a view of the garden, as well as the barn’s unique structure. The extension, that links both barn and farmhouse, is deliberately contemporary in appearance to ensure that the historic buildings remain legible. It’s low-rise, built into the sloping garden and particularly lightweight in appearance. Floor-to-ceiling glass sits on a plinth of semi-knapped flint, rooting the intervention into the garden. A ribbon of black steel, with shallow peaks and troughs hovers above. The form of this ribbon draws inspiration from the distinctive black timber-clad gables that characterise the farmhouse and the surrounding outbuildings of the old farmstead. Internally the addition’s structure is exposed, much like the historic timber framed structure of the farmhouse and the barn. The interiors are tactile, defined by texture and pattern and inspired by the characteristics of the old farmstead. Miles Kelsey, associate, Will Gamble ArchitectsAdvertisement Client’s view We bought the farmhouse as a family home to move out of our two-bed flat in north London. Will visited the farmhouse with us whilst we were working through the purchase to understand what we were looking to do and went on to support us through each stage. The farmhouse was a combination of the original 16th century timber-framed building that had been added to with unattractive, unusable, and poorly planned extensions that meant the house was completely disconnected from the garden. Will and Miles transformed the whole house including moving the front door, converting an adjacent barn and building the modern extension as our kitchen and dining room that makes the best of the garden and views. The process that Will and Miles ran was a perfect balance of what we wanted, Sophie’s specific tastes and creativity combined with the benefit of the architects views and what they have done before. What really stood out to us was the way they worked with the council during the planning process so we got consent for almost everything we wanted, expressing their own views but ensuring we were always leading the process and the attention to detail during the build stage. Overall we are incredibly happy with what Will and Miles helped us create and the way they led us through the whole process.   Source:Will Gamble Architects Project data Location North Hertfordshire Start on site April 2023 Completion February 2025 Gross internal floor area 320m2 Form of contract or procurement route JCT MW Building Contract. Design-Bid-Build Architect Will Gamble Architects Client Private Structural engineer Axiom Structures Principal designer Will Gamble Architects Main contractor Elite Construction #will #gamble #architects #restores #extends
    WWW.ARCHITECTSJOURNAL.CO.UK
    Will Gamble Architects restores and extends Hertfordshire farmhouse
    The farmhouse, Flint Farm, in North Hertfordshire, was in poor condition with a number of unsympathetic additions that had altered its character over the years. Will Gamble Architects was appointed to restore and extend it for a young couple who wanted to transform it into their long-term family home and improve the house’s relationship with its garden and wider farmyard setting. While the original brief had been to replace an existing conservatory with a new extension, the practice encouraged the client to extend by integrating an adjacent barn into the envelope of the reworked house, changing the way the property was used.Advertisement Existing unsympathetic extensions were removed and the internal layout was reconfigured, with a new linking element added between the barn and farmhouse. The series of internal spaces that has been created is designed to retain the character of the historic listed property. Architect’s view The barn was sensitively restored and converted into an informal living space. Its timber-framed structure was refurbished and left exposed to celebrate the historic fabric of the barn and the craftsmanship of its original construction. A contemporary picture window with parts of the historic timber frame exposed within its reveals frames a view of the garden, as well as the barn’s unique structure. The extension, that links both barn and farmhouse, is deliberately contemporary in appearance to ensure that the historic buildings remain legible. It’s low-rise, built into the sloping garden and particularly lightweight in appearance. Floor-to-ceiling glass sits on a plinth of semi-knapped flint, rooting the intervention into the garden. A ribbon of black steel, with shallow peaks and troughs hovers above. The form of this ribbon draws inspiration from the distinctive black timber-clad gables that characterise the farmhouse and the surrounding outbuildings of the old farmstead. Internally the addition’s structure is exposed, much like the historic timber framed structure of the farmhouse and the barn. The interiors are tactile, defined by texture and pattern and inspired by the characteristics of the old farmstead. Miles Kelsey, associate, Will Gamble ArchitectsAdvertisement Client’s view We bought the farmhouse as a family home to move out of our two-bed flat in north London. Will visited the farmhouse with us whilst we were working through the purchase to understand what we were looking to do and went on to support us through each stage. The farmhouse was a combination of the original 16th century timber-framed building that had been added to with unattractive, unusable, and poorly planned extensions that meant the house was completely disconnected from the garden. Will and Miles transformed the whole house including moving the front door, converting an adjacent barn and building the modern extension as our kitchen and dining room that makes the best of the garden and views. The process that Will and Miles ran was a perfect balance of what we wanted, Sophie’s specific tastes and creativity combined with the benefit of the architects views and what they have done before. What really stood out to us was the way they worked with the council during the planning process so we got consent for almost everything we wanted, expressing their own views but ensuring we were always leading the process and the attention to detail during the build stage. Overall we are incredibly happy with what Will and Miles helped us create and the way they led us through the whole process.   Source:Will Gamble Architects Project data Location North Hertfordshire Start on site April 2023 Completion February 2025 Gross internal floor area 320m2 Form of contract or procurement route JCT MW Building Contract. Design-Bid-Build Architect Will Gamble Architects Client Private Structural engineer Axiom Structures Principal designer Will Gamble Architects Main contractor Elite Construction
    0 Σχόλια 0 Μοιράστηκε
  • 48 Rustic Living Room Ideas For the Coziest Family Space

    With its comfortable, laid-back decorating vibes, no room says “come and sit awhile” or “aah, I’m home” quite like a beautifully inviting rustic and cozy living room. Whether you live in a farmhouse, cabin, cottage, a new-build in the suburbs, or even a city apartment—rustic living room ideas bring a certain homespun style that ranges from downright traditional to modern and chic.Here at Country Living, we’ve discovered that the very best classic and country rustic living room ideas begin with good ol’ tried-and-true character-rich decor. We're talking reclaimed wood, stone focal points, and a casual mix of natural textures and materials. More modern rustic living room ideas include a less-is-more approach with calming neutral color palettes and clean-lined furniture. Paint colors, fabrics, and accessories in grays, browns, and greens pulled from nature make for the just-right warmth—all simple rustic living room ideas at their finest. So relax and sink into our best country rustic living room ideas from some of our all-time favorite Country Living house tours!Here are more creative ways to make your home feel rustic and cozy:1Fill the Room With CharacterSean LitchfieldFrom floor to ceiling and wall to wall, this rustic living room packs in loads of character. Comfy leather and upholstered furniture, a vintage patterned rug, and a blue and yellow painted cupboard found on Facebook marketplace sit well together against a backdrop of rustic wood.2Source Local MaterialsLincoln BarbourIn this beautifully rustic Mississippi barn. the owners sourced local wood materials from a nearby military depot to clad the walls and ceiling, bringing maximum warmth and texture. Large windows let in loads of natural light during the day, while a chandelier and mounted sconces make for a romantic glow come nighttime.RELATED: These Wood Ceiling Ideas Bring Country Charm to Any RoomTOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below3Pick a Cozy Paint ColorAlpha Smoot for Country LivingThis cozy living room has a built-in warmth, thanks to saturated navy blue walls. Its handsomely worn floorboards, doors, mantel, and warming cabinet above the fireplace complement the dark blue beautifully. The fire and candlelight emit a magical glow.Get the Look:Wall Paint Color: Dark Navy by BehrTOUR THE ENTIRE HOUSE4Lay a Comfy RugSara Ligorria-TrampWhat's cozier than a roaring fire on a cool night? A soft, fuzzy rug in front of it! The fireplace features mantel made from a tree felled on-site and white Zellige tile. The artwork is a vintage find paired with a contemporary painting.TOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below5Embrace Log Cabin DetailsLisa FloodIn this stunning Wyoming log cabin, the family usually gathers in the wonderfully rustic great room. Its cozy factor is off the charts, thanks country decorating classics like unpainted log walls and beams, a woodburning stove, textural rugs, and a sweet swing that hangs from the ceiling. Get the Look:Swing: The Oak & Rope CompanyTOUR THE ENTIRE HOUSE6Wrap a Room in WoodMarta Xochilt PerezIn this rustic and cozy cabin, an original fieldstone fireplace creates the warmest welcome. A pair of cushy leather sofas piled with pillows blankets face off, anchoring the wood-wrapped space, and providing the perfect perches for game night. TOUR THE ENTIRE HOUSE Advertisement - Continue Reading Below7Build an Rustic Stone Accent WallMarta Xochilt Perez for Country LivingThis impressive wall of moss rock surrounds the fireplace. Chiseled stone corbels provide mantel supports. On cool nights, you can count on a roaring fire! Throughout the home, carved timbers, rough-cut stone, and walls of windows reflect a combination of the homeowners’ Scandinavian heritage and Irish roots.TOUR THE ENTIRE HOUSE8Go Big in a Small SpaceEmily FollowillThis tiny living room is packed with so much character. Designer James Farmer added decorative oomph with a large tobacco basket, an art-forward fireplace screen, and natural design elements like plants. Details like arranging the paneling on the diagonal to “point” upward enhance the vertical space. Says James, “Tall ceilings, bold plant arrangements, and large light fixtures have even more impact in a small home. Play with scale to find what feels right.” Advertisement - Continue Reading Below9Mix and Match FurnitureLincoln BarbourFor the ultimate collected-over-time vibe, forgo matching furniture. Here, a wingback chair and a spool chair look right at home in this living room. Other period-appropriate decor found in this 100-year-old home: painted paneled walls, exposed ceiling beams, and a rustic mantel wood.TOUR THE ENTIRE HOUSE 10Let There Be LightChristopher DibbleWe put this family room in the “rustic light” category. For a top-to-bottom cabin-like feel, designer Max Humphrey wrapped the space in eight-foot knotty pine planks on the ceiling and walls. A clear coat of polyurethane protects the wood while letting its natural color shine through. Colorful national park posters, globes, camp grounds signage, and a linen modern sectional create a hip yet homey living space.Advertisement - Continue Reading Below11Customize a Focal PointHomeowners Victoria and Marcus Ford’s vision of a custom wood fireplace surround included open shelves and striking floor-to-ceiling firewood nooks. “We figured go big or go home,” says Victoria. Brass sconces provide a library-like touch, and a custom frame has the TV looking picture-perfect above the mantel.Get the Look:Wall and Trim Paint: Endless Sea by Sherwin-WilliamsCeiling Paint: Oyster White by Sherwin-WilliamsTOUR THE ENTIRE SPACE12Incorporate Rustic Furniture FindsAnnie SchlechterTopped with a plaid cushion, a rustic yellow daybed nestled in the corner makes for the coziest spot to take in lake views. The 22-foot cathedral ceilings are clad in wood, warming up this lofty open-concept space designed by Amy Meier that also includes a dining area and kitchen.TOUR THE ENTIRE HOUSE Advertisement - Continue Reading Below13Paint the FloorsDane Tashima for Country LivingWhile the homeowners of this New Jersey dairy barn were able to salvage the structure’s original knotty beams, the walls and floors in the soaring 25-foot-high space needed to be replaced. Simple poplar planks painted white got the job done affordably. A new cast-iron pellet stove warms the space with a rustic, authentic look. Get the Look:Wall and Floor Paint Color: Alabaster by Sherwin-WilliamsTOUR THE ENTIRE HOUSE14Tell the BackstorySean LitchfieldWhere possible, the original Eastern Hemlock posts and beams of this 1819 Maine barn were carefully preserved when, in 1999, the structure was disassembled and then reassembled several miles down the road. Hand-split slabs of Maine graniteand brick were used to fabricate the massive woodburning fireplace. The walls and floors are lined in rough-hewn, nonuniform wood planks. The sofa table, made from an old piece of barn wood found on the farm, shows off collections of books, ceramics, and shells.Advertisement - Continue Reading Below15Use Old Materials for New BuildsBrie WilliamsIn this new build, reclaimed materials create instant patina for a warm and welcoming family room. Here’s what makes it rustic: reclaimed beams came from an 1800s mill in Massachusetts mill; log skins salvaged from old Midwest barns; North Carolina stone on the fireplace. A soft palette for the furniture and window treatments was inspired by the antique rug that covers the ottoman.TOUR THE ENTIRE HOUSE 16Balance Natural Wood with ColorNick JohnsonA pretty blue on the fireplace and in the fabrics balances the overall rustic vibe in this country house. “I wanted this room to feel rich and cozy and warm—the kind of place you’d sit by the fire to read a book,” says Erica Harrison of Detroit-based design firm Hudson and Sterling.TOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below17Make It WorkHelen NormanDespite the renovation challenges, this cozy sitting area situated just off the open kitchen works. The fireplace, which had to be rebuilt from the inside, was covered in stucco to balance all the exposed brick that was discovered underneath damaged drywall. For attic access, a ladder that was found in a barn on the property gets the job done in lieu of stairs. On the other side of the fireplace, a sturdy wooden bookshelf replaces an existing one that was crumbling.18Paint It WhiteZIO AND SONSFor the ultimate modern farmhouse vibe, start with an all-white palette, like in this home of designer Anthony D’Argenzio. This allows you to layer in character-rich architectural elements, like wide-planked wood floors and ceiling beams. A comfy sectional piled with pillows balances perfectly with hard elements, like the wood-and-iron coffee table, handmade oak stump side table, and a round iron chandelier. The hanging chair in the corner provides a wink to this serene design. RELATED: The Best Warm White Paint Colors For Every Room in Your HouseAdvertisement - Continue Reading Below19Leave Materials NaturalJames MerrellRustic meets cozy in this cabin that features walls constructed of hand-hewn logs, a stone fireplace, exposed ceiling beams, and a pair of comfy armchairs. Leaving all materials in their natural finish and unpainted contributes to the overall homespun feel.RELATED: The Best Places to Find or Buy Reclaimed Wood Near You20Choose Neutral FurnishingsSeth SmootIn this California living room, a comfortable collection of neutral furnishings complements the home’s rustic redwood walls. The solid sofa and barrel chairs that are upholstered in linen leave room for visual delights, like the wicker and fringe lamps, an antique rug, a patterned ottoman, and piles of pillows.Jennifer KopfJennifer Kopf is the Executive Editor of Country Living. She also covers antiques and collecting.Amy MitchellManaging EditorAmy Mitchell is the managing editor for VERANDA and Country Living, where she writes articles on a variety of topics—decorating and design, gardens, and holidays. Amy’s experience in the shelter magazine category spans more than 20 years, as she’s previously held positions at Coastal Living and Cottage Living. Her personal pursuits include cooking, gardening, and hunting her favorite tag sale spots for the next piece of Pyrex for her prized collection.
    #rustic #living #room #ideas #coziest
    48 Rustic Living Room Ideas For the Coziest Family Space
    With its comfortable, laid-back decorating vibes, no room says “come and sit awhile” or “aah, I’m home” quite like a beautifully inviting rustic and cozy living room. Whether you live in a farmhouse, cabin, cottage, a new-build in the suburbs, or even a city apartment—rustic living room ideas bring a certain homespun style that ranges from downright traditional to modern and chic.Here at Country Living, we’ve discovered that the very best classic and country rustic living room ideas begin with good ol’ tried-and-true character-rich decor. We're talking reclaimed wood, stone focal points, and a casual mix of natural textures and materials. More modern rustic living room ideas include a less-is-more approach with calming neutral color palettes and clean-lined furniture. Paint colors, fabrics, and accessories in grays, browns, and greens pulled from nature make for the just-right warmth—all simple rustic living room ideas at their finest. So relax and sink into our best country rustic living room ideas from some of our all-time favorite Country Living house tours!Here are more creative ways to make your home feel rustic and cozy:1Fill the Room With CharacterSean LitchfieldFrom floor to ceiling and wall to wall, this rustic living room packs in loads of character. Comfy leather and upholstered furniture, a vintage patterned rug, and a blue and yellow painted cupboard found on Facebook marketplace sit well together against a backdrop of rustic wood.2Source Local MaterialsLincoln BarbourIn this beautifully rustic Mississippi barn. the owners sourced local wood materials from a nearby military depot to clad the walls and ceiling, bringing maximum warmth and texture. Large windows let in loads of natural light during the day, while a chandelier and mounted sconces make for a romantic glow come nighttime.RELATED: These Wood Ceiling Ideas Bring Country Charm to Any RoomTOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below3Pick a Cozy Paint ColorAlpha Smoot for Country LivingThis cozy living room has a built-in warmth, thanks to saturated navy blue walls. Its handsomely worn floorboards, doors, mantel, and warming cabinet above the fireplace complement the dark blue beautifully. The fire and candlelight emit a magical glow.Get the Look:Wall Paint Color: Dark Navy by BehrTOUR THE ENTIRE HOUSE4Lay a Comfy RugSara Ligorria-TrampWhat's cozier than a roaring fire on a cool night? A soft, fuzzy rug in front of it! The fireplace features mantel made from a tree felled on-site and white Zellige tile. The artwork is a vintage find paired with a contemporary painting.TOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below5Embrace Log Cabin DetailsLisa FloodIn this stunning Wyoming log cabin, the family usually gathers in the wonderfully rustic great room. Its cozy factor is off the charts, thanks country decorating classics like unpainted log walls and beams, a woodburning stove, textural rugs, and a sweet swing that hangs from the ceiling. Get the Look:Swing: The Oak & Rope CompanyTOUR THE ENTIRE HOUSE6Wrap a Room in WoodMarta Xochilt PerezIn this rustic and cozy cabin, an original fieldstone fireplace creates the warmest welcome. A pair of cushy leather sofas piled with pillows blankets face off, anchoring the wood-wrapped space, and providing the perfect perches for game night. TOUR THE ENTIRE HOUSE Advertisement - Continue Reading Below7Build an Rustic Stone Accent WallMarta Xochilt Perez for Country LivingThis impressive wall of moss rock surrounds the fireplace. Chiseled stone corbels provide mantel supports. On cool nights, you can count on a roaring fire! Throughout the home, carved timbers, rough-cut stone, and walls of windows reflect a combination of the homeowners’ Scandinavian heritage and Irish roots.TOUR THE ENTIRE HOUSE8Go Big in a Small SpaceEmily FollowillThis tiny living room is packed with so much character. Designer James Farmer added decorative oomph with a large tobacco basket, an art-forward fireplace screen, and natural design elements like plants. Details like arranging the paneling on the diagonal to “point” upward enhance the vertical space. Says James, “Tall ceilings, bold plant arrangements, and large light fixtures have even more impact in a small home. Play with scale to find what feels right.” Advertisement - Continue Reading Below9Mix and Match FurnitureLincoln BarbourFor the ultimate collected-over-time vibe, forgo matching furniture. Here, a wingback chair and a spool chair look right at home in this living room. Other period-appropriate decor found in this 100-year-old home: painted paneled walls, exposed ceiling beams, and a rustic mantel wood.TOUR THE ENTIRE HOUSE 10Let There Be LightChristopher DibbleWe put this family room in the “rustic light” category. For a top-to-bottom cabin-like feel, designer Max Humphrey wrapped the space in eight-foot knotty pine planks on the ceiling and walls. A clear coat of polyurethane protects the wood while letting its natural color shine through. Colorful national park posters, globes, camp grounds signage, and a linen modern sectional create a hip yet homey living space.Advertisement - Continue Reading Below11Customize a Focal PointHomeowners Victoria and Marcus Ford’s vision of a custom wood fireplace surround included open shelves and striking floor-to-ceiling firewood nooks. “We figured go big or go home,” says Victoria. Brass sconces provide a library-like touch, and a custom frame has the TV looking picture-perfect above the mantel.Get the Look:Wall and Trim Paint: Endless Sea by Sherwin-WilliamsCeiling Paint: Oyster White by Sherwin-WilliamsTOUR THE ENTIRE SPACE12Incorporate Rustic Furniture FindsAnnie SchlechterTopped with a plaid cushion, a rustic yellow daybed nestled in the corner makes for the coziest spot to take in lake views. The 22-foot cathedral ceilings are clad in wood, warming up this lofty open-concept space designed by Amy Meier that also includes a dining area and kitchen.TOUR THE ENTIRE HOUSE Advertisement - Continue Reading Below13Paint the FloorsDane Tashima for Country LivingWhile the homeowners of this New Jersey dairy barn were able to salvage the structure’s original knotty beams, the walls and floors in the soaring 25-foot-high space needed to be replaced. Simple poplar planks painted white got the job done affordably. A new cast-iron pellet stove warms the space with a rustic, authentic look. Get the Look:Wall and Floor Paint Color: Alabaster by Sherwin-WilliamsTOUR THE ENTIRE HOUSE14Tell the BackstorySean LitchfieldWhere possible, the original Eastern Hemlock posts and beams of this 1819 Maine barn were carefully preserved when, in 1999, the structure was disassembled and then reassembled several miles down the road. Hand-split slabs of Maine graniteand brick were used to fabricate the massive woodburning fireplace. The walls and floors are lined in rough-hewn, nonuniform wood planks. The sofa table, made from an old piece of barn wood found on the farm, shows off collections of books, ceramics, and shells.Advertisement - Continue Reading Below15Use Old Materials for New BuildsBrie WilliamsIn this new build, reclaimed materials create instant patina for a warm and welcoming family room. Here’s what makes it rustic: reclaimed beams came from an 1800s mill in Massachusetts mill; log skins salvaged from old Midwest barns; North Carolina stone on the fireplace. A soft palette for the furniture and window treatments was inspired by the antique rug that covers the ottoman.TOUR THE ENTIRE HOUSE 16Balance Natural Wood with ColorNick JohnsonA pretty blue on the fireplace and in the fabrics balances the overall rustic vibe in this country house. “I wanted this room to feel rich and cozy and warm—the kind of place you’d sit by the fire to read a book,” says Erica Harrison of Detroit-based design firm Hudson and Sterling.TOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below17Make It WorkHelen NormanDespite the renovation challenges, this cozy sitting area situated just off the open kitchen works. The fireplace, which had to be rebuilt from the inside, was covered in stucco to balance all the exposed brick that was discovered underneath damaged drywall. For attic access, a ladder that was found in a barn on the property gets the job done in lieu of stairs. On the other side of the fireplace, a sturdy wooden bookshelf replaces an existing one that was crumbling.18Paint It WhiteZIO AND SONSFor the ultimate modern farmhouse vibe, start with an all-white palette, like in this home of designer Anthony D’Argenzio. This allows you to layer in character-rich architectural elements, like wide-planked wood floors and ceiling beams. A comfy sectional piled with pillows balances perfectly with hard elements, like the wood-and-iron coffee table, handmade oak stump side table, and a round iron chandelier. The hanging chair in the corner provides a wink to this serene design. RELATED: The Best Warm White Paint Colors For Every Room in Your HouseAdvertisement - Continue Reading Below19Leave Materials NaturalJames MerrellRustic meets cozy in this cabin that features walls constructed of hand-hewn logs, a stone fireplace, exposed ceiling beams, and a pair of comfy armchairs. Leaving all materials in their natural finish and unpainted contributes to the overall homespun feel.RELATED: The Best Places to Find or Buy Reclaimed Wood Near You20Choose Neutral FurnishingsSeth SmootIn this California living room, a comfortable collection of neutral furnishings complements the home’s rustic redwood walls. The solid sofa and barrel chairs that are upholstered in linen leave room for visual delights, like the wicker and fringe lamps, an antique rug, a patterned ottoman, and piles of pillows.Jennifer KopfJennifer Kopf is the Executive Editor of Country Living. She also covers antiques and collecting.Amy MitchellManaging EditorAmy Mitchell is the managing editor for VERANDA and Country Living, where she writes articles on a variety of topics—decorating and design, gardens, and holidays. Amy’s experience in the shelter magazine category spans more than 20 years, as she’s previously held positions at Coastal Living and Cottage Living. Her personal pursuits include cooking, gardening, and hunting her favorite tag sale spots for the next piece of Pyrex for her prized collection. #rustic #living #room #ideas #coziest
    WWW.COUNTRYLIVING.COM
    48 Rustic Living Room Ideas For the Coziest Family Space
    With its comfortable, laid-back decorating vibes, no room says “come and sit awhile” or “aah, I’m home” quite like a beautifully inviting rustic and cozy living room. Whether you live in a farmhouse, cabin, cottage, a new-build in the suburbs, or even a city apartment—rustic living room ideas bring a certain homespun style that ranges from downright traditional to modern and chic.Here at Country Living, we’ve discovered that the very best classic and country rustic living room ideas begin with good ol’ tried-and-true character-rich decor. We're talking reclaimed wood, stone focal points (there are so many rustic style living room ideas with cozy fireplaces!), and a casual mix of natural textures and materials (think wood and woven furniture, perfectly worn leather sofas, vintage wool rugs laid atop natural sisal). More modern rustic living room ideas include a less-is-more approach with calming neutral color palettes and clean-lined furniture. Paint colors, fabrics, and accessories in grays, browns, and greens pulled from nature make for the just-right warmth—all simple rustic living room ideas at their finest. So relax and sink into our best country rustic living room ideas from some of our all-time favorite Country Living house tours!Here are more creative ways to make your home feel rustic and cozy:1Fill the Room With CharacterSean LitchfieldFrom floor to ceiling and wall to wall, this rustic living room packs in loads of character. Comfy leather and upholstered furniture, a vintage patterned rug, and a blue and yellow painted cupboard found on Facebook marketplace sit well together against a backdrop of rustic wood.2Source Local MaterialsLincoln BarbourIn this beautifully rustic Mississippi barn. the owners sourced local wood materials from a nearby military depot to clad the walls and ceiling, bringing maximum warmth and texture. Large windows let in loads of natural light during the day, while a chandelier and mounted sconces make for a romantic glow come nighttime.RELATED: These Wood Ceiling Ideas Bring Country Charm to Any RoomTOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below3Pick a Cozy Paint ColorAlpha Smoot for Country LivingThis cozy living room has a built-in warmth, thanks to saturated navy blue walls (“It’s sort of a gentleman’s navy,” says homeowner Justin Reis). Its handsomely worn floorboards, doors, mantel, and warming cabinet above the fireplace complement the dark blue beautifully. The fire and candlelight emit a magical glow.Get the Look:Wall Paint Color: Dark Navy by BehrTOUR THE ENTIRE HOUSE4Lay a Comfy RugSara Ligorria-TrampWhat's cozier than a roaring fire on a cool night? A soft, fuzzy rug in front of it! The fireplace features mantel made from a tree felled on-site and white Zellige tile. The artwork is a vintage find paired with a contemporary painting.TOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below5Embrace Log Cabin DetailsLisa FloodIn this stunning Wyoming log cabin, the family usually gathers in the wonderfully rustic great room. Its cozy factor is off the charts, thanks country decorating classics like unpainted log walls and beams, a woodburning stove, textural rugs, and a sweet swing that hangs from the ceiling. Get the Look:Swing: The Oak & Rope CompanyTOUR THE ENTIRE HOUSE6Wrap a Room in WoodMarta Xochilt PerezIn this rustic and cozy cabin, an original fieldstone fireplace creates the warmest welcome. A pair of cushy leather sofas piled with pillows blankets face off, anchoring the wood-wrapped space, and providing the perfect perches for game night. TOUR THE ENTIRE HOUSE Advertisement - Continue Reading Below7Build an Rustic Stone Accent WallMarta Xochilt Perez for Country LivingThis impressive wall of moss rock surrounds the fireplace. Chiseled stone corbels provide mantel supports. On cool nights, you can count on a roaring fire! Throughout the home, carved timbers, rough-cut stone, and walls of windows reflect a combination of the homeowners’ Scandinavian heritage and Irish roots.TOUR THE ENTIRE HOUSE8Go Big in a Small SpaceEmily FollowillThis tiny living room is packed with so much character. Designer James Farmer added decorative oomph with a large tobacco basket, an art-forward fireplace screen, and natural design elements like plants. Details like arranging the paneling on the diagonal to “point” upward enhance the vertical space. Says James, “Tall ceilings, bold plant arrangements, and large light fixtures have even more impact in a small home. Play with scale to find what feels right.” Advertisement - Continue Reading Below9Mix and Match FurnitureLincoln BarbourFor the ultimate collected-over-time vibe, forgo matching furniture. Here, a wingback chair and a spool chair look right at home in this living room. Other period-appropriate decor found in this 100-year-old home: painted paneled walls, exposed ceiling beams, and a rustic mantel wood.TOUR THE ENTIRE HOUSE 10Let There Be Light (Wood)Christopher DibbleWe put this family room in the “rustic light” category. For a top-to-bottom cabin-like feel, designer Max Humphrey wrapped the space in eight-foot knotty pine planks on the ceiling and walls. A clear coat of polyurethane protects the wood while letting its natural color shine through (a stain would’ve darkened the room). Colorful national park posters, globes, camp grounds signage, and a linen modern sectional create a hip yet homey living space.Advertisement - Continue Reading Below11Customize a Focal PointHomeowners Victoria and Marcus Ford’s vision of a custom wood fireplace surround included open shelves and striking floor-to-ceiling firewood nooks (our favorite detail!). “We figured go big or go home,” says Victoria. Brass sconces provide a library-like touch, and a custom frame has the TV looking picture-perfect above the mantel.Get the Look:Wall and Trim Paint: Endless Sea by Sherwin-WilliamsCeiling Paint: Oyster White by Sherwin-WilliamsTOUR THE ENTIRE SPACE12Incorporate Rustic Furniture FindsAnnie SchlechterTopped with a plaid cushion, a rustic yellow daybed nestled in the corner makes for the coziest spot to take in lake views. The 22-foot cathedral ceilings are clad in wood, warming up this lofty open-concept space designed by Amy Meier that also includes a dining area and kitchen.TOUR THE ENTIRE HOUSE Advertisement - Continue Reading Below13Paint the FloorsDane Tashima for Country LivingWhile the homeowners of this New Jersey dairy barn were able to salvage the structure’s original knotty beams, the walls and floors in the soaring 25-foot-high space needed to be replaced. Simple poplar planks painted white got the job done affordably. A new cast-iron pellet stove warms the space with a rustic, authentic look. Get the Look:Wall and Floor Paint Color: Alabaster by Sherwin-WilliamsTOUR THE ENTIRE HOUSE14Tell the BackstorySean LitchfieldWhere possible, the original Eastern Hemlock posts and beams of this 1819 Maine barn were carefully preserved when, in 1999, the structure was disassembled and then reassembled several miles down the road. Hand-split slabs of Maine granite (some from the barn's original foundation) and brick were used to fabricate the massive woodburning fireplace. The walls and floors are lined in rough-hewn, nonuniform wood planks. The sofa table, made from an old piece of barn wood found on the farm, shows off collections of books, ceramics, and shells.Advertisement - Continue Reading Below15Use Old Materials for New BuildsBrie WilliamsIn this new build, reclaimed materials create instant patina for a warm and welcoming family room. Here’s what makes it rustic: reclaimed beams came from an 1800s mill in Massachusetts mill; log skins salvaged from old Midwest barns; North Carolina stone on the fireplace. A soft palette for the furniture and window treatments was inspired by the antique rug that covers the ottoman.TOUR THE ENTIRE HOUSE 16Balance Natural Wood with ColorNick JohnsonA pretty blue on the fireplace and in the fabrics balances the overall rustic vibe in this country house. “I wanted this room to feel rich and cozy and warm—the kind of place you’d sit by the fire to read a book,” says Erica Harrison of Detroit-based design firm Hudson and Sterling.TOUR THE ENTIRE HOUSEAdvertisement - Continue Reading Below17Make It WorkHelen NormanDespite the renovation challenges, this cozy sitting area situated just off the open kitchen works. The fireplace, which had to be rebuilt from the inside, was covered in stucco to balance all the exposed brick that was discovered underneath damaged drywall. For attic access, a ladder that was found in a barn on the property gets the job done in lieu of stairs. On the other side of the fireplace, a sturdy wooden bookshelf replaces an existing one that was crumbling.18Paint It WhiteZIO AND SONSFor the ultimate modern farmhouse vibe, start with an all-white palette, like in this home of designer Anthony D’Argenzio. This allows you to layer in character-rich architectural elements, like wide-planked wood floors and ceiling beams. A comfy sectional piled with pillows balances perfectly with hard elements, like the wood-and-iron coffee table, handmade oak stump side table, and a round iron chandelier. The hanging chair in the corner provides a wink to this serene design. RELATED: The Best Warm White Paint Colors For Every Room in Your HouseAdvertisement - Continue Reading Below19Leave Materials NaturalJames MerrellRustic meets cozy in this cabin that features walls constructed of hand-hewn logs, a stone fireplace, exposed ceiling beams, and a pair of comfy armchairs. Leaving all materials in their natural finish and unpainted contributes to the overall homespun feel.RELATED: The Best Places to Find or Buy Reclaimed Wood Near You20Choose Neutral FurnishingsSeth SmootIn this California living room, a comfortable collection of neutral furnishings complements the home’s rustic redwood walls. The solid sofa and barrel chairs that are upholstered in linen leave room for visual delights, like the wicker and fringe lamps, an antique rug, a patterned ottoman, and piles of pillows.Jennifer KopfJennifer Kopf is the Executive Editor of Country Living. She also covers antiques and collecting.Amy MitchellManaging EditorAmy Mitchell is the managing editor for VERANDA and Country Living, where she writes articles on a variety of topics—decorating and design, gardens, and holidays. Amy’s experience in the shelter magazine category spans more than 20 years, as she’s previously held positions at Coastal Living and Cottage Living. Her personal pursuits include cooking, gardening, and hunting her favorite tag sale spots for the next piece of Pyrex for her prized collection.
    0 Σχόλια 0 Μοιράστηκε
  • Looking Back at Two Classics: ILM Deploys the Fleet in ‘Star Trek: First Contact’ and ‘Rogue One: A Star Wars Story’

    Guided by visual effects supervisor John Knoll, ILM embraced continually evolving methodologies to craft breathtaking visual effects for the iconic space battles in First Contact and Rogue One.
    By Jay Stobie
    Visual effects supervisor John Knollconfers with modelmakers Kim Smith and John Goodson with the miniature of the U.S.S. Enterprise-E during production of Star Trek: First Contact.
    Bolstered by visual effects from Industrial Light & Magic, Star Trek: First Contactand Rogue One: A Star Wars Storypropelled their respective franchises to new heights. While Star Trek Generationswelcomed Captain Jean-Luc Picard’screw to the big screen, First Contact stood as the first Star Trek feature that did not focus on its original captain, the legendary James T. Kirk. Similarly, though Rogue One immediately preceded the events of Star Wars: A New Hope, it was set apart from the episodic Star Wars films and launched an era of storytelling outside of the main Skywalker saga that has gone on to include Solo: A Star Wars Story, The Mandalorian, Andor, Ahsoka, The Acolyte, and more.
    The two films also shared a key ILM contributor, John Knoll, who served as visual effects supervisor on both projects, as well as an executive producer on Rogue One. Currently, ILM’s executive creative director and senior visual effects supervisor, Knoll – who also conceived the initial framework for Rogue One’s story – guided ILM as it brought its talents to bear on these sci-fi and fantasy epics. The work involved crafting two spectacular starship-packed space clashes – First Contact’s Battle of Sector 001 and Rogue One’s Battle of Scarif. Although these iconic installments were released roughly two decades apart, they represent a captivating case study of how ILM’s approach to visual effects has evolved over time. With this in mind, let’s examine the films’ unforgettable space battles through the lens of fascinating in-universe parallels and the ILM-produced fleets that face off near Earth and Scarif.
    A final frame from the Battle of Scarif in Rogue One: A Star Wars Story.
    A Context for Conflict
    In First Contact, the United Federation of Planets – a 200-year-old interstellar government consisting of more than 150 member worlds – braces itself for an invasion by the Borg – an overwhelmingly powerful collective composed of cybernetic beings who devastate entire planets by assimilating their biological populations and technological innovations. The Borg only send a single vessel, a massive cube containing thousands of hive-minded drones and their queen, pushing the Federation’s Starfleet defenders to Earth’s doorstep. Conversely, in Rogue One, the Rebel Alliance – a fledgling coalition of freedom fighters – seeks to undermine and overthrow the stalwart Galactic Empire – a totalitarian regime preparing to tighten its grip on the galaxy by revealing a horrifying superweapon. A rebel team infiltrates a top-secret vault on Scarif in a bid to steal plans to that battle station, the dreaded Death Star, with hopes of exploiting a vulnerability in its design.
    On the surface, the situations could not seem to be more disparate, particularly in terms of the Federation’s well-established prestige and the Rebel Alliance’s haphazardly organized factions. Yet, upon closer inspection, the spaceborne conflicts at Earth and Scarif are linked by a vital commonality. The threat posed by the Borg is well-known to the Federation, but the sudden intrusion upon their space takes its defenses by surprise. Starfleet assembles any vessel within range – including antiquated Oberth-class science ships – to intercept the Borg cube in the Typhon Sector, only to be forced back to Earth on the edge of defeat. The unsanctioned mission to Scarif with Jyn Ersoand Cassian Andorand the sudden need to take down the planet’s shield gate propels the Rebel Alliance fleet into rushing to their rescue with everything from their flagship Profundity to GR-75 medium transports. Whether Federation or Rebel Alliance, these fleets gather in last-ditch efforts to oppose enemies who would embrace their eradication – the Battles of Sector 001 and Scarif are fights for survival.
    From Physical to Digital
    By the time Jonathan Frakes was selected to direct First Contact, Star Trek’s reliance on constructing traditional physical modelsfor its features was gradually giving way to innovative computer graphicsmodels, resulting in the film’s use of both techniques. “If one of the ships was to be seen full-screen and at length,” associate visual effects supervisor George Murphy told Cinefex’s Kevin H. Martin, “we knew it would be done as a stage model. Ships that would be doing a lot of elaborate maneuvers in space battle scenes would be created digitally.” In fact, physical and CG versions of the U.S.S. Enterprise-E appear in the film, with the latter being harnessed in shots involving the vessel’s entry into a temporal vortex at the conclusion of the Battle of Sector 001.
    Despite the technological leaps that ILM pioneered in the decades between First Contact and Rogue One, they considered filming physical miniatures for certain ship-related shots in the latter film. ILM considered filming physical miniatures for certain ship-related shots in Rogue One. The feature’s fleets were ultimately created digitally to allow for changes throughout post-production. “If it’s a photographed miniature element, it’s not possible to go back and make adjustments. So it’s the additional flexibility that comes with the computer graphics models that’s very attractive to many people,” John Knoll relayed to writer Jon Witmer at American Cinematographer’s TheASC.com.
    However, Knoll aimed to develop computer graphics that retained the same high-quality details as their physical counterparts, leading ILM to employ a modern approach to a time-honored modelmaking tactic. “I also wanted to emulate the kit-bashing aesthetic that had been part of Star Wars from the very beginning, where a lot of mechanical detail had been added onto the ships by using little pieces from plastic model kits,” explained Knoll in his chat with TheASC.com. For Rogue One, ILM replicated the process by obtaining such kits, scanning their parts, building a computer graphics library, and applying the CG parts to digitally modeled ships. “I’m very happy to say it was super-successful,” concluded Knoll. “I think a lot of our digital models look like they are motion-control models.”
    John Knollconfers with Kim Smith and John Goodson with the miniature of the U.S.S. Enterprise-E during production of Star Trek: First Contact.
    Legendary Lineages
    In First Contact, Captain Picard commanded a brand-new vessel, the Sovereign-class U.S.S. Enterprise-E, continuing the celebrated starship’s legacy in terms of its famous name and design aesthetic. Designed by John Eaves and developed into blueprints by Rick Sternbach, the Enterprise-E was built into a 10-foot physical model by ILM model project supervisor John Goodson and his shop’s talented team. ILM infused the ship with extraordinary detail, including viewports equipped with backlit set images from the craft’s predecessor, the U.S.S. Enterprise-D. For the vessel’s larger windows, namely those associated with the observation lounge and arboretum, ILM took a painstakingly practical approach to match the interiors shown with the real-world set pieces. “We filled that area of the model with tiny, micro-scale furniture,” Goodson informed Cinefex, “including tables and chairs.”
    Rogue One’s rebel team initially traversed the galaxy in a U-wing transport/gunship, which, much like the Enterprise-E, was a unique vessel that nonetheless channeled a certain degree of inspiration from a classic design. Lucasfilm’s Doug Chiang, a co-production designer for Rogue One, referred to the U-wing as the film’s “Huey helicopter version of an X-wing” in the Designing Rogue One bonus featurette on Disney+ before revealing that, “Towards the end of the design cycle, we actually decided that maybe we should put in more X-wing features. And so we took the X-wing engines and literally mounted them onto the configuration that we had going.” Modeled by ILM digital artist Colie Wertz, the U-wing’s final computer graphics design subtly incorporated these X-wing influences to give the transport a distinctive feel without making the craft seem out of place within the rebel fleet.
    While ILM’s work on the Enterprise-E’s viewports offered a compelling view toward the ship’s interior, a breakthrough LED setup for Rogue One permitted ILM to obtain realistic lighting on actors as they looked out from their ships and into the space around them. “All of our major spaceship cockpit scenes were done that way, with the gimbal in this giant horseshoe of LED panels we got fromVER, and we prepared graphics that went on the screens,” John Knoll shared with American Cinematographer’s Benjamin B and Jon D. Witmer. Furthermore, in Disney+’s Rogue One: Digital Storytelling bonus featurette, visual effects producer Janet Lewin noted, “For the actors, I think, in the space battle cockpits, for them to be able to see what was happening in the battle brought a higher level of accuracy to their performance.”
    The U.S.S. Enterprise-E in Star Trek: First Contact.
    Familiar Foes
    To transport First Contact’s Borg invaders, John Goodson’s team at ILM resurrected the Borg cube design previously seen in Star Trek: The Next Generationand Star Trek: Deep Space Nine, creating a nearly three-foot physical model to replace the one from the series. Art consultant and ILM veteran Bill George proposed that the cube’s seemingly straightforward layout be augmented with a complex network of photo-etched brass, a suggestion which produced a jagged surface and offered a visual that was both intricate and menacing. ILM also developed a two-foot motion-control model for a Borg sphere, a brand-new auxiliary vessel that emerged from the cube. “We vacuformed about 15 different patterns that conformed to this spherical curve and covered those with a lot of molded and cast pieces. Then we added tons of acid-etched brass over it, just like we had on the cube,” Goodson outlined to Cinefex’s Kevin H. Martin.
    As for Rogue One’s villainous fleet, reproducing the original trilogy’s Death Star and Imperial Star Destroyers centered upon translating physical models into digital assets. Although ILM no longer possessed A New Hope’s three-foot Death Star shooting model, John Knoll recreated the station’s surface paneling by gathering archival images, and as he spelled out to writer Joe Fordham in Cinefex, “I pieced all the images together. I unwrapped them into texture space and projected them onto a sphere with a trench. By doing that with enough pictures, I got pretty complete coverage of the original model, and that became a template upon which to redraw very high-resolution texture maps. Every panel, every vertical striped line, I matched from a photograph. It was as accurate as it was possible to be as a reproduction of the original model.”
    Knoll’s investigative eye continued to pay dividends when analyzing the three-foot and eight-foot Star Destroyer motion-control models, which had been built for A New Hope and Star Wars: The Empire Strikes Back, respectively. “Our general mantra was, ‘Match your memory of it more than the reality,’ because sometimes you go look at the actual prop in the archive building or you look back at the actual shot from the movie, and you go, ‘Oh, I remember it being a little better than that,’” Knoll conveyed to TheASC.com. This philosophy motivated ILM to combine elements from those two physical models into a single digital design. “Generally, we copied the three-footer for details like the superstructure on the top of the bridge, but then we copied the internal lighting plan from the eight-footer,” Knoll explained. “And then the upper surface of the three-footer was relatively undetailed because there were no shots that saw it closely, so we took a lot of the high-detail upper surface from the eight-footer. So it’s this amalgam of the two models, but the goal was to try to make it look like you remember it from A New Hope.”
    A final frame from Rogue One: A Star Wars Story.
    Forming Up the Fleets
    In addition to the U.S.S. Enterprise-E, the Battle of Sector 001 debuted numerous vessels representing four new Starfleet ship classes – the Akira, Steamrunner, Saber, and Norway – all designed by ILM visual effects art director Alex Jaeger. “Since we figured a lot of the background action in the space battle would be done with computer graphics ships that needed to be built from scratch anyway, I realized that there was no reason not to do some new designs,” John Knoll told American Cinematographer writer Ron Magid. Used in previous Star Trek projects, older physical models for the Oberth and Nebula classes were mixed into the fleet for good measure, though the vast majority of the armada originated as computer graphics.
    Over at Scarif, ILM portrayed the Rebel Alliance forces with computer graphics models of fresh designs, live-action versions of Star Wars Rebels’ VCX-100 light freighter Ghost and Hammerhead corvettes, and Star Wars staples. These ships face off against two Imperial Star Destroyers and squadrons of TIE fighters, and – upon their late arrival to the battle – Darth Vader’s Star Destroyer and the Death Star. The Tantive IV, a CR90 corvette more popularly referred to as a blockade runner, made its own special cameo at the tail end of the fight. As Princess Leia Organa’spersonal ship, the Tantive IV received the Death Star plans and fled the scene, destined to be captured by Vader’s Star Destroyer at the beginning of A New Hope. And, while we’re on the subject of intricate starship maneuvers and space-based choreography…
    Although the First Contact team could plan visual effects shots with animated storyboards, ILM supplied Gareth Edwards with a next-level virtual viewfinder that allowed the director to select his shots by immersing himself among Rogue One’s ships in real time. “What we wanted to do is give Gareth the opportunity to shoot his space battles and other all-digital scenes the same way he shoots his live-action. Then he could go in with this sort of virtual viewfinder and view the space battle going on, and figure out what the best angle was to shoot those ships from,” senior animation supervisor Hal Hickel described in the Rogue One: Digital Storytelling featurette. Hickel divulged that the sequence involving the dish array docking with the Death Star was an example of the “spontaneous discovery of great angles,” as the scene was never storyboarded or previsualized.
    Visual effects supervisor John Knoll with director Gareth Edwards during production of Rogue One: A Star Wars Story.
    Tough Little Ships
    The Federation and Rebel Alliance each deployed “tough little ships”in their respective conflicts, namely the U.S.S. Defiant from Deep Space Nine and the Tantive IV from A New Hope. VisionArt had already built a CG Defiant for the Deep Space Nine series, but ILM upgraded the model with images gathered from the ship’s three-foot physical model. A similar tactic was taken to bring the Tantive IV into the digital realm for Rogue One. “This was the Blockade Runner. This was the most accurate 1:1 reproduction we could possibly have made,” model supervisor Russell Paul declared to Cinefex’s Joe Fordham. “We did an extensive photo reference shoot and photogrammetry re-creation of the miniature. From there, we built it out as accurately as possible.” Speaking of sturdy ships, if you look very closely, you can spot a model of the Millennium Falcon flashing across the background as the U.S.S. Defiant makes an attack run on the Borg cube at the Battle of Sector 001!
    Exploration and Hope
    The in-universe ramifications that materialize from the Battles of Sector 001 and Scarif are monumental. The destruction of the Borg cube compels the Borg Queen to travel back in time in an attempt to vanquish Earth before the Federation can even be formed, but Captain Picard and the Enterprise-E foil the plot and end up helping their 21st century ancestors make “first contact” with another species, the logic-revering Vulcans. The post-Scarif benefits take longer to play out for the Rebel Alliance, but the theft of the Death Star plans eventually leads to the superweapon’s destruction. The Galactic Civil War is far from over, but Scarif is a significant step in the Alliance’s effort to overthrow the Empire.
    The visual effects ILM provided for First Contact and Rogue One contributed significantly to the critical and commercial acclaim both pictures enjoyed, a victory reflecting the relentless dedication, tireless work ethic, and innovative spirit embodied by visual effects supervisor John Knoll and ILM’s entire staff. While being interviewed for The Making of Star Trek: First Contact, actor Patrick Stewart praised ILM’s invaluable influence, emphasizing, “ILM was with us, on this movie, almost every day on set. There is so much that they are involved in.” And, regardless of your personal preferences – phasers or lasers, photon torpedoes or proton torpedoes, warp speed or hyperspace – perhaps Industrial Light & Magic’s ability to infuse excitement into both franchises demonstrates that Star Trek and Star Wars encompass themes that are not competitive, but compatible. After all, what goes together better than exploration and hope?

    Jay Stobieis a writer, author, and consultant who has contributed articles to ILM.com, Skysound.com, Star Wars Insider, StarWars.com, Star Trek Explorer, Star Trek Magazine, and StarTrek.com. Jay loves sci-fi, fantasy, and film, and you can learn more about him by visiting JayStobie.com or finding him on Twitter, Instagram, and other social media platforms at @StobiesGalaxy.
    #looking #back #two #classics #ilm
    Looking Back at Two Classics: ILM Deploys the Fleet in ‘Star Trek: First Contact’ and ‘Rogue One: A Star Wars Story’
    Guided by visual effects supervisor John Knoll, ILM embraced continually evolving methodologies to craft breathtaking visual effects for the iconic space battles in First Contact and Rogue One. By Jay Stobie Visual effects supervisor John Knollconfers with modelmakers Kim Smith and John Goodson with the miniature of the U.S.S. Enterprise-E during production of Star Trek: First Contact. Bolstered by visual effects from Industrial Light & Magic, Star Trek: First Contactand Rogue One: A Star Wars Storypropelled their respective franchises to new heights. While Star Trek Generationswelcomed Captain Jean-Luc Picard’screw to the big screen, First Contact stood as the first Star Trek feature that did not focus on its original captain, the legendary James T. Kirk. Similarly, though Rogue One immediately preceded the events of Star Wars: A New Hope, it was set apart from the episodic Star Wars films and launched an era of storytelling outside of the main Skywalker saga that has gone on to include Solo: A Star Wars Story, The Mandalorian, Andor, Ahsoka, The Acolyte, and more. The two films also shared a key ILM contributor, John Knoll, who served as visual effects supervisor on both projects, as well as an executive producer on Rogue One. Currently, ILM’s executive creative director and senior visual effects supervisor, Knoll – who also conceived the initial framework for Rogue One’s story – guided ILM as it brought its talents to bear on these sci-fi and fantasy epics. The work involved crafting two spectacular starship-packed space clashes – First Contact’s Battle of Sector 001 and Rogue One’s Battle of Scarif. Although these iconic installments were released roughly two decades apart, they represent a captivating case study of how ILM’s approach to visual effects has evolved over time. With this in mind, let’s examine the films’ unforgettable space battles through the lens of fascinating in-universe parallels and the ILM-produced fleets that face off near Earth and Scarif. A final frame from the Battle of Scarif in Rogue One: A Star Wars Story. A Context for Conflict In First Contact, the United Federation of Planets – a 200-year-old interstellar government consisting of more than 150 member worlds – braces itself for an invasion by the Borg – an overwhelmingly powerful collective composed of cybernetic beings who devastate entire planets by assimilating their biological populations and technological innovations. The Borg only send a single vessel, a massive cube containing thousands of hive-minded drones and their queen, pushing the Federation’s Starfleet defenders to Earth’s doorstep. Conversely, in Rogue One, the Rebel Alliance – a fledgling coalition of freedom fighters – seeks to undermine and overthrow the stalwart Galactic Empire – a totalitarian regime preparing to tighten its grip on the galaxy by revealing a horrifying superweapon. A rebel team infiltrates a top-secret vault on Scarif in a bid to steal plans to that battle station, the dreaded Death Star, with hopes of exploiting a vulnerability in its design. On the surface, the situations could not seem to be more disparate, particularly in terms of the Federation’s well-established prestige and the Rebel Alliance’s haphazardly organized factions. Yet, upon closer inspection, the spaceborne conflicts at Earth and Scarif are linked by a vital commonality. The threat posed by the Borg is well-known to the Federation, but the sudden intrusion upon their space takes its defenses by surprise. Starfleet assembles any vessel within range – including antiquated Oberth-class science ships – to intercept the Borg cube in the Typhon Sector, only to be forced back to Earth on the edge of defeat. The unsanctioned mission to Scarif with Jyn Ersoand Cassian Andorand the sudden need to take down the planet’s shield gate propels the Rebel Alliance fleet into rushing to their rescue with everything from their flagship Profundity to GR-75 medium transports. Whether Federation or Rebel Alliance, these fleets gather in last-ditch efforts to oppose enemies who would embrace their eradication – the Battles of Sector 001 and Scarif are fights for survival. From Physical to Digital By the time Jonathan Frakes was selected to direct First Contact, Star Trek’s reliance on constructing traditional physical modelsfor its features was gradually giving way to innovative computer graphicsmodels, resulting in the film’s use of both techniques. “If one of the ships was to be seen full-screen and at length,” associate visual effects supervisor George Murphy told Cinefex’s Kevin H. Martin, “we knew it would be done as a stage model. Ships that would be doing a lot of elaborate maneuvers in space battle scenes would be created digitally.” In fact, physical and CG versions of the U.S.S. Enterprise-E appear in the film, with the latter being harnessed in shots involving the vessel’s entry into a temporal vortex at the conclusion of the Battle of Sector 001. Despite the technological leaps that ILM pioneered in the decades between First Contact and Rogue One, they considered filming physical miniatures for certain ship-related shots in the latter film. ILM considered filming physical miniatures for certain ship-related shots in Rogue One. The feature’s fleets were ultimately created digitally to allow for changes throughout post-production. “If it’s a photographed miniature element, it’s not possible to go back and make adjustments. So it’s the additional flexibility that comes with the computer graphics models that’s very attractive to many people,” John Knoll relayed to writer Jon Witmer at American Cinematographer’s TheASC.com. However, Knoll aimed to develop computer graphics that retained the same high-quality details as their physical counterparts, leading ILM to employ a modern approach to a time-honored modelmaking tactic. “I also wanted to emulate the kit-bashing aesthetic that had been part of Star Wars from the very beginning, where a lot of mechanical detail had been added onto the ships by using little pieces from plastic model kits,” explained Knoll in his chat with TheASC.com. For Rogue One, ILM replicated the process by obtaining such kits, scanning their parts, building a computer graphics library, and applying the CG parts to digitally modeled ships. “I’m very happy to say it was super-successful,” concluded Knoll. “I think a lot of our digital models look like they are motion-control models.” John Knollconfers with Kim Smith and John Goodson with the miniature of the U.S.S. Enterprise-E during production of Star Trek: First Contact. Legendary Lineages In First Contact, Captain Picard commanded a brand-new vessel, the Sovereign-class U.S.S. Enterprise-E, continuing the celebrated starship’s legacy in terms of its famous name and design aesthetic. Designed by John Eaves and developed into blueprints by Rick Sternbach, the Enterprise-E was built into a 10-foot physical model by ILM model project supervisor John Goodson and his shop’s talented team. ILM infused the ship with extraordinary detail, including viewports equipped with backlit set images from the craft’s predecessor, the U.S.S. Enterprise-D. For the vessel’s larger windows, namely those associated with the observation lounge and arboretum, ILM took a painstakingly practical approach to match the interiors shown with the real-world set pieces. “We filled that area of the model with tiny, micro-scale furniture,” Goodson informed Cinefex, “including tables and chairs.” Rogue One’s rebel team initially traversed the galaxy in a U-wing transport/gunship, which, much like the Enterprise-E, was a unique vessel that nonetheless channeled a certain degree of inspiration from a classic design. Lucasfilm’s Doug Chiang, a co-production designer for Rogue One, referred to the U-wing as the film’s “Huey helicopter version of an X-wing” in the Designing Rogue One bonus featurette on Disney+ before revealing that, “Towards the end of the design cycle, we actually decided that maybe we should put in more X-wing features. And so we took the X-wing engines and literally mounted them onto the configuration that we had going.” Modeled by ILM digital artist Colie Wertz, the U-wing’s final computer graphics design subtly incorporated these X-wing influences to give the transport a distinctive feel without making the craft seem out of place within the rebel fleet. While ILM’s work on the Enterprise-E’s viewports offered a compelling view toward the ship’s interior, a breakthrough LED setup for Rogue One permitted ILM to obtain realistic lighting on actors as they looked out from their ships and into the space around them. “All of our major spaceship cockpit scenes were done that way, with the gimbal in this giant horseshoe of LED panels we got fromVER, and we prepared graphics that went on the screens,” John Knoll shared with American Cinematographer’s Benjamin B and Jon D. Witmer. Furthermore, in Disney+’s Rogue One: Digital Storytelling bonus featurette, visual effects producer Janet Lewin noted, “For the actors, I think, in the space battle cockpits, for them to be able to see what was happening in the battle brought a higher level of accuracy to their performance.” The U.S.S. Enterprise-E in Star Trek: First Contact. Familiar Foes To transport First Contact’s Borg invaders, John Goodson’s team at ILM resurrected the Borg cube design previously seen in Star Trek: The Next Generationand Star Trek: Deep Space Nine, creating a nearly three-foot physical model to replace the one from the series. Art consultant and ILM veteran Bill George proposed that the cube’s seemingly straightforward layout be augmented with a complex network of photo-etched brass, a suggestion which produced a jagged surface and offered a visual that was both intricate and menacing. ILM also developed a two-foot motion-control model for a Borg sphere, a brand-new auxiliary vessel that emerged from the cube. “We vacuformed about 15 different patterns that conformed to this spherical curve and covered those with a lot of molded and cast pieces. Then we added tons of acid-etched brass over it, just like we had on the cube,” Goodson outlined to Cinefex’s Kevin H. Martin. As for Rogue One’s villainous fleet, reproducing the original trilogy’s Death Star and Imperial Star Destroyers centered upon translating physical models into digital assets. Although ILM no longer possessed A New Hope’s three-foot Death Star shooting model, John Knoll recreated the station’s surface paneling by gathering archival images, and as he spelled out to writer Joe Fordham in Cinefex, “I pieced all the images together. I unwrapped them into texture space and projected them onto a sphere with a trench. By doing that with enough pictures, I got pretty complete coverage of the original model, and that became a template upon which to redraw very high-resolution texture maps. Every panel, every vertical striped line, I matched from a photograph. It was as accurate as it was possible to be as a reproduction of the original model.” Knoll’s investigative eye continued to pay dividends when analyzing the three-foot and eight-foot Star Destroyer motion-control models, which had been built for A New Hope and Star Wars: The Empire Strikes Back, respectively. “Our general mantra was, ‘Match your memory of it more than the reality,’ because sometimes you go look at the actual prop in the archive building or you look back at the actual shot from the movie, and you go, ‘Oh, I remember it being a little better than that,’” Knoll conveyed to TheASC.com. This philosophy motivated ILM to combine elements from those two physical models into a single digital design. “Generally, we copied the three-footer for details like the superstructure on the top of the bridge, but then we copied the internal lighting plan from the eight-footer,” Knoll explained. “And then the upper surface of the three-footer was relatively undetailed because there were no shots that saw it closely, so we took a lot of the high-detail upper surface from the eight-footer. So it’s this amalgam of the two models, but the goal was to try to make it look like you remember it from A New Hope.” A final frame from Rogue One: A Star Wars Story. Forming Up the Fleets In addition to the U.S.S. Enterprise-E, the Battle of Sector 001 debuted numerous vessels representing four new Starfleet ship classes – the Akira, Steamrunner, Saber, and Norway – all designed by ILM visual effects art director Alex Jaeger. “Since we figured a lot of the background action in the space battle would be done with computer graphics ships that needed to be built from scratch anyway, I realized that there was no reason not to do some new designs,” John Knoll told American Cinematographer writer Ron Magid. Used in previous Star Trek projects, older physical models for the Oberth and Nebula classes were mixed into the fleet for good measure, though the vast majority of the armada originated as computer graphics. Over at Scarif, ILM portrayed the Rebel Alliance forces with computer graphics models of fresh designs, live-action versions of Star Wars Rebels’ VCX-100 light freighter Ghost and Hammerhead corvettes, and Star Wars staples. These ships face off against two Imperial Star Destroyers and squadrons of TIE fighters, and – upon their late arrival to the battle – Darth Vader’s Star Destroyer and the Death Star. The Tantive IV, a CR90 corvette more popularly referred to as a blockade runner, made its own special cameo at the tail end of the fight. As Princess Leia Organa’spersonal ship, the Tantive IV received the Death Star plans and fled the scene, destined to be captured by Vader’s Star Destroyer at the beginning of A New Hope. And, while we’re on the subject of intricate starship maneuvers and space-based choreography… Although the First Contact team could plan visual effects shots with animated storyboards, ILM supplied Gareth Edwards with a next-level virtual viewfinder that allowed the director to select his shots by immersing himself among Rogue One’s ships in real time. “What we wanted to do is give Gareth the opportunity to shoot his space battles and other all-digital scenes the same way he shoots his live-action. Then he could go in with this sort of virtual viewfinder and view the space battle going on, and figure out what the best angle was to shoot those ships from,” senior animation supervisor Hal Hickel described in the Rogue One: Digital Storytelling featurette. Hickel divulged that the sequence involving the dish array docking with the Death Star was an example of the “spontaneous discovery of great angles,” as the scene was never storyboarded or previsualized. Visual effects supervisor John Knoll with director Gareth Edwards during production of Rogue One: A Star Wars Story. Tough Little Ships The Federation and Rebel Alliance each deployed “tough little ships”in their respective conflicts, namely the U.S.S. Defiant from Deep Space Nine and the Tantive IV from A New Hope. VisionArt had already built a CG Defiant for the Deep Space Nine series, but ILM upgraded the model with images gathered from the ship’s three-foot physical model. A similar tactic was taken to bring the Tantive IV into the digital realm for Rogue One. “This was the Blockade Runner. This was the most accurate 1:1 reproduction we could possibly have made,” model supervisor Russell Paul declared to Cinefex’s Joe Fordham. “We did an extensive photo reference shoot and photogrammetry re-creation of the miniature. From there, we built it out as accurately as possible.” Speaking of sturdy ships, if you look very closely, you can spot a model of the Millennium Falcon flashing across the background as the U.S.S. Defiant makes an attack run on the Borg cube at the Battle of Sector 001! Exploration and Hope The in-universe ramifications that materialize from the Battles of Sector 001 and Scarif are monumental. The destruction of the Borg cube compels the Borg Queen to travel back in time in an attempt to vanquish Earth before the Federation can even be formed, but Captain Picard and the Enterprise-E foil the plot and end up helping their 21st century ancestors make “first contact” with another species, the logic-revering Vulcans. The post-Scarif benefits take longer to play out for the Rebel Alliance, but the theft of the Death Star plans eventually leads to the superweapon’s destruction. The Galactic Civil War is far from over, but Scarif is a significant step in the Alliance’s effort to overthrow the Empire. The visual effects ILM provided for First Contact and Rogue One contributed significantly to the critical and commercial acclaim both pictures enjoyed, a victory reflecting the relentless dedication, tireless work ethic, and innovative spirit embodied by visual effects supervisor John Knoll and ILM’s entire staff. While being interviewed for The Making of Star Trek: First Contact, actor Patrick Stewart praised ILM’s invaluable influence, emphasizing, “ILM was with us, on this movie, almost every day on set. There is so much that they are involved in.” And, regardless of your personal preferences – phasers or lasers, photon torpedoes or proton torpedoes, warp speed or hyperspace – perhaps Industrial Light & Magic’s ability to infuse excitement into both franchises demonstrates that Star Trek and Star Wars encompass themes that are not competitive, but compatible. After all, what goes together better than exploration and hope? – Jay Stobieis a writer, author, and consultant who has contributed articles to ILM.com, Skysound.com, Star Wars Insider, StarWars.com, Star Trek Explorer, Star Trek Magazine, and StarTrek.com. Jay loves sci-fi, fantasy, and film, and you can learn more about him by visiting JayStobie.com or finding him on Twitter, Instagram, and other social media platforms at @StobiesGalaxy. #looking #back #two #classics #ilm
    WWW.ILM.COM
    Looking Back at Two Classics: ILM Deploys the Fleet in ‘Star Trek: First Contact’ and ‘Rogue One: A Star Wars Story’
    Guided by visual effects supervisor John Knoll, ILM embraced continually evolving methodologies to craft breathtaking visual effects for the iconic space battles in First Contact and Rogue One. By Jay Stobie Visual effects supervisor John Knoll (right) confers with modelmakers Kim Smith and John Goodson with the miniature of the U.S.S. Enterprise-E during production of Star Trek: First Contact (Credit: ILM). Bolstered by visual effects from Industrial Light & Magic, Star Trek: First Contact (1996) and Rogue One: A Star Wars Story (2016) propelled their respective franchises to new heights. While Star Trek Generations (1994) welcomed Captain Jean-Luc Picard’s (Patrick Stewart) crew to the big screen, First Contact stood as the first Star Trek feature that did not focus on its original captain, the legendary James T. Kirk (William Shatner). Similarly, though Rogue One immediately preceded the events of Star Wars: A New Hope (1977), it was set apart from the episodic Star Wars films and launched an era of storytelling outside of the main Skywalker saga that has gone on to include Solo: A Star Wars Story (2018), The Mandalorian (2019-23), Andor (2022-25), Ahsoka (2023), The Acolyte (2024), and more. The two films also shared a key ILM contributor, John Knoll, who served as visual effects supervisor on both projects, as well as an executive producer on Rogue One. Currently, ILM’s executive creative director and senior visual effects supervisor, Knoll – who also conceived the initial framework for Rogue One’s story – guided ILM as it brought its talents to bear on these sci-fi and fantasy epics. The work involved crafting two spectacular starship-packed space clashes – First Contact’s Battle of Sector 001 and Rogue One’s Battle of Scarif. Although these iconic installments were released roughly two decades apart, they represent a captivating case study of how ILM’s approach to visual effects has evolved over time. With this in mind, let’s examine the films’ unforgettable space battles through the lens of fascinating in-universe parallels and the ILM-produced fleets that face off near Earth and Scarif. A final frame from the Battle of Scarif in Rogue One: A Star Wars Story (Credit: ILM & Lucasfilm). A Context for Conflict In First Contact, the United Federation of Planets – a 200-year-old interstellar government consisting of more than 150 member worlds – braces itself for an invasion by the Borg – an overwhelmingly powerful collective composed of cybernetic beings who devastate entire planets by assimilating their biological populations and technological innovations. The Borg only send a single vessel, a massive cube containing thousands of hive-minded drones and their queen, pushing the Federation’s Starfleet defenders to Earth’s doorstep. Conversely, in Rogue One, the Rebel Alliance – a fledgling coalition of freedom fighters – seeks to undermine and overthrow the stalwart Galactic Empire – a totalitarian regime preparing to tighten its grip on the galaxy by revealing a horrifying superweapon. A rebel team infiltrates a top-secret vault on Scarif in a bid to steal plans to that battle station, the dreaded Death Star, with hopes of exploiting a vulnerability in its design. On the surface, the situations could not seem to be more disparate, particularly in terms of the Federation’s well-established prestige and the Rebel Alliance’s haphazardly organized factions. Yet, upon closer inspection, the spaceborne conflicts at Earth and Scarif are linked by a vital commonality. The threat posed by the Borg is well-known to the Federation, but the sudden intrusion upon their space takes its defenses by surprise. Starfleet assembles any vessel within range – including antiquated Oberth-class science ships – to intercept the Borg cube in the Typhon Sector, only to be forced back to Earth on the edge of defeat. The unsanctioned mission to Scarif with Jyn Erso (Felicity Jones) and Cassian Andor (Diego Luna) and the sudden need to take down the planet’s shield gate propels the Rebel Alliance fleet into rushing to their rescue with everything from their flagship Profundity to GR-75 medium transports. Whether Federation or Rebel Alliance, these fleets gather in last-ditch efforts to oppose enemies who would embrace their eradication – the Battles of Sector 001 and Scarif are fights for survival. From Physical to Digital By the time Jonathan Frakes was selected to direct First Contact, Star Trek’s reliance on constructing traditional physical models (many of which were built by ILM) for its features was gradually giving way to innovative computer graphics (CG) models, resulting in the film’s use of both techniques. “If one of the ships was to be seen full-screen and at length,” associate visual effects supervisor George Murphy told Cinefex’s Kevin H. Martin, “we knew it would be done as a stage model. Ships that would be doing a lot of elaborate maneuvers in space battle scenes would be created digitally.” In fact, physical and CG versions of the U.S.S. Enterprise-E appear in the film, with the latter being harnessed in shots involving the vessel’s entry into a temporal vortex at the conclusion of the Battle of Sector 001. Despite the technological leaps that ILM pioneered in the decades between First Contact and Rogue One, they considered filming physical miniatures for certain ship-related shots in the latter film. ILM considered filming physical miniatures for certain ship-related shots in Rogue One. The feature’s fleets were ultimately created digitally to allow for changes throughout post-production. “If it’s a photographed miniature element, it’s not possible to go back and make adjustments. So it’s the additional flexibility that comes with the computer graphics models that’s very attractive to many people,” John Knoll relayed to writer Jon Witmer at American Cinematographer’s TheASC.com. However, Knoll aimed to develop computer graphics that retained the same high-quality details as their physical counterparts, leading ILM to employ a modern approach to a time-honored modelmaking tactic. “I also wanted to emulate the kit-bashing aesthetic that had been part of Star Wars from the very beginning, where a lot of mechanical detail had been added onto the ships by using little pieces from plastic model kits,” explained Knoll in his chat with TheASC.com. For Rogue One, ILM replicated the process by obtaining such kits, scanning their parts, building a computer graphics library, and applying the CG parts to digitally modeled ships. “I’m very happy to say it was super-successful,” concluded Knoll. “I think a lot of our digital models look like they are motion-control models.” John Knoll (second from left) confers with Kim Smith and John Goodson with the miniature of the U.S.S. Enterprise-E during production of Star Trek: First Contact (Credit: ILM). Legendary Lineages In First Contact, Captain Picard commanded a brand-new vessel, the Sovereign-class U.S.S. Enterprise-E, continuing the celebrated starship’s legacy in terms of its famous name and design aesthetic. Designed by John Eaves and developed into blueprints by Rick Sternbach, the Enterprise-E was built into a 10-foot physical model by ILM model project supervisor John Goodson and his shop’s talented team. ILM infused the ship with extraordinary detail, including viewports equipped with backlit set images from the craft’s predecessor, the U.S.S. Enterprise-D. For the vessel’s larger windows, namely those associated with the observation lounge and arboretum, ILM took a painstakingly practical approach to match the interiors shown with the real-world set pieces. “We filled that area of the model with tiny, micro-scale furniture,” Goodson informed Cinefex, “including tables and chairs.” Rogue One’s rebel team initially traversed the galaxy in a U-wing transport/gunship, which, much like the Enterprise-E, was a unique vessel that nonetheless channeled a certain degree of inspiration from a classic design. Lucasfilm’s Doug Chiang, a co-production designer for Rogue One, referred to the U-wing as the film’s “Huey helicopter version of an X-wing” in the Designing Rogue One bonus featurette on Disney+ before revealing that, “Towards the end of the design cycle, we actually decided that maybe we should put in more X-wing features. And so we took the X-wing engines and literally mounted them onto the configuration that we had going.” Modeled by ILM digital artist Colie Wertz, the U-wing’s final computer graphics design subtly incorporated these X-wing influences to give the transport a distinctive feel without making the craft seem out of place within the rebel fleet. While ILM’s work on the Enterprise-E’s viewports offered a compelling view toward the ship’s interior, a breakthrough LED setup for Rogue One permitted ILM to obtain realistic lighting on actors as they looked out from their ships and into the space around them. “All of our major spaceship cockpit scenes were done that way, with the gimbal in this giant horseshoe of LED panels we got from [equipment vendor] VER, and we prepared graphics that went on the screens,” John Knoll shared with American Cinematographer’s Benjamin B and Jon D. Witmer. Furthermore, in Disney+’s Rogue One: Digital Storytelling bonus featurette, visual effects producer Janet Lewin noted, “For the actors, I think, in the space battle cockpits, for them to be able to see what was happening in the battle brought a higher level of accuracy to their performance.” The U.S.S. Enterprise-E in Star Trek: First Contact (Credit: Paramount). Familiar Foes To transport First Contact’s Borg invaders, John Goodson’s team at ILM resurrected the Borg cube design previously seen in Star Trek: The Next Generation (1987) and Star Trek: Deep Space Nine (1993), creating a nearly three-foot physical model to replace the one from the series. Art consultant and ILM veteran Bill George proposed that the cube’s seemingly straightforward layout be augmented with a complex network of photo-etched brass, a suggestion which produced a jagged surface and offered a visual that was both intricate and menacing. ILM also developed a two-foot motion-control model for a Borg sphere, a brand-new auxiliary vessel that emerged from the cube. “We vacuformed about 15 different patterns that conformed to this spherical curve and covered those with a lot of molded and cast pieces. Then we added tons of acid-etched brass over it, just like we had on the cube,” Goodson outlined to Cinefex’s Kevin H. Martin. As for Rogue One’s villainous fleet, reproducing the original trilogy’s Death Star and Imperial Star Destroyers centered upon translating physical models into digital assets. Although ILM no longer possessed A New Hope’s three-foot Death Star shooting model, John Knoll recreated the station’s surface paneling by gathering archival images, and as he spelled out to writer Joe Fordham in Cinefex, “I pieced all the images together. I unwrapped them into texture space and projected them onto a sphere with a trench. By doing that with enough pictures, I got pretty complete coverage of the original model, and that became a template upon which to redraw very high-resolution texture maps. Every panel, every vertical striped line, I matched from a photograph. It was as accurate as it was possible to be as a reproduction of the original model.” Knoll’s investigative eye continued to pay dividends when analyzing the three-foot and eight-foot Star Destroyer motion-control models, which had been built for A New Hope and Star Wars: The Empire Strikes Back (1980), respectively. “Our general mantra was, ‘Match your memory of it more than the reality,’ because sometimes you go look at the actual prop in the archive building or you look back at the actual shot from the movie, and you go, ‘Oh, I remember it being a little better than that,’” Knoll conveyed to TheASC.com. This philosophy motivated ILM to combine elements from those two physical models into a single digital design. “Generally, we copied the three-footer for details like the superstructure on the top of the bridge, but then we copied the internal lighting plan from the eight-footer,” Knoll explained. “And then the upper surface of the three-footer was relatively undetailed because there were no shots that saw it closely, so we took a lot of the high-detail upper surface from the eight-footer. So it’s this amalgam of the two models, but the goal was to try to make it look like you remember it from A New Hope.” A final frame from Rogue One: A Star Wars Story (Credit: ILM & Lucasfilm). Forming Up the Fleets In addition to the U.S.S. Enterprise-E, the Battle of Sector 001 debuted numerous vessels representing four new Starfleet ship classes – the Akira, Steamrunner, Saber, and Norway – all designed by ILM visual effects art director Alex Jaeger. “Since we figured a lot of the background action in the space battle would be done with computer graphics ships that needed to be built from scratch anyway, I realized that there was no reason not to do some new designs,” John Knoll told American Cinematographer writer Ron Magid. Used in previous Star Trek projects, older physical models for the Oberth and Nebula classes were mixed into the fleet for good measure, though the vast majority of the armada originated as computer graphics. Over at Scarif, ILM portrayed the Rebel Alliance forces with computer graphics models of fresh designs (the MC75 cruiser Profundity and U-wings), live-action versions of Star Wars Rebels’ VCX-100 light freighter Ghost and Hammerhead corvettes, and Star Wars staples (Nebulon-B frigates, X-wings, Y-wings, and more). These ships face off against two Imperial Star Destroyers and squadrons of TIE fighters, and – upon their late arrival to the battle – Darth Vader’s Star Destroyer and the Death Star. The Tantive IV, a CR90 corvette more popularly referred to as a blockade runner, made its own special cameo at the tail end of the fight. As Princess Leia Organa’s (Carrie Fisher and Ingvild Deila) personal ship, the Tantive IV received the Death Star plans and fled the scene, destined to be captured by Vader’s Star Destroyer at the beginning of A New Hope. And, while we’re on the subject of intricate starship maneuvers and space-based choreography… Although the First Contact team could plan visual effects shots with animated storyboards, ILM supplied Gareth Edwards with a next-level virtual viewfinder that allowed the director to select his shots by immersing himself among Rogue One’s ships in real time. “What we wanted to do is give Gareth the opportunity to shoot his space battles and other all-digital scenes the same way he shoots his live-action. Then he could go in with this sort of virtual viewfinder and view the space battle going on, and figure out what the best angle was to shoot those ships from,” senior animation supervisor Hal Hickel described in the Rogue One: Digital Storytelling featurette. Hickel divulged that the sequence involving the dish array docking with the Death Star was an example of the “spontaneous discovery of great angles,” as the scene was never storyboarded or previsualized. Visual effects supervisor John Knoll with director Gareth Edwards during production of Rogue One: A Star Wars Story (Credit: ILM & Lucasfilm). Tough Little Ships The Federation and Rebel Alliance each deployed “tough little ships” (an endearing description Commander William T. Riker [Jonathan Frakes] bestowed upon the U.S.S. Defiant in First Contact) in their respective conflicts, namely the U.S.S. Defiant from Deep Space Nine and the Tantive IV from A New Hope. VisionArt had already built a CG Defiant for the Deep Space Nine series, but ILM upgraded the model with images gathered from the ship’s three-foot physical model. A similar tactic was taken to bring the Tantive IV into the digital realm for Rogue One. “This was the Blockade Runner. This was the most accurate 1:1 reproduction we could possibly have made,” model supervisor Russell Paul declared to Cinefex’s Joe Fordham. “We did an extensive photo reference shoot and photogrammetry re-creation of the miniature. From there, we built it out as accurately as possible.” Speaking of sturdy ships, if you look very closely, you can spot a model of the Millennium Falcon flashing across the background as the U.S.S. Defiant makes an attack run on the Borg cube at the Battle of Sector 001! Exploration and Hope The in-universe ramifications that materialize from the Battles of Sector 001 and Scarif are monumental. The destruction of the Borg cube compels the Borg Queen to travel back in time in an attempt to vanquish Earth before the Federation can even be formed, but Captain Picard and the Enterprise-E foil the plot and end up helping their 21st century ancestors make “first contact” with another species, the logic-revering Vulcans. The post-Scarif benefits take longer to play out for the Rebel Alliance, but the theft of the Death Star plans eventually leads to the superweapon’s destruction. The Galactic Civil War is far from over, but Scarif is a significant step in the Alliance’s effort to overthrow the Empire. The visual effects ILM provided for First Contact and Rogue One contributed significantly to the critical and commercial acclaim both pictures enjoyed, a victory reflecting the relentless dedication, tireless work ethic, and innovative spirit embodied by visual effects supervisor John Knoll and ILM’s entire staff. While being interviewed for The Making of Star Trek: First Contact, actor Patrick Stewart praised ILM’s invaluable influence, emphasizing, “ILM was with us, on this movie, almost every day on set. There is so much that they are involved in.” And, regardless of your personal preferences – phasers or lasers, photon torpedoes or proton torpedoes, warp speed or hyperspace – perhaps Industrial Light & Magic’s ability to infuse excitement into both franchises demonstrates that Star Trek and Star Wars encompass themes that are not competitive, but compatible. After all, what goes together better than exploration and hope? – Jay Stobie (he/him) is a writer, author, and consultant who has contributed articles to ILM.com, Skysound.com, Star Wars Insider, StarWars.com, Star Trek Explorer, Star Trek Magazine, and StarTrek.com. Jay loves sci-fi, fantasy, and film, and you can learn more about him by visiting JayStobie.com or finding him on Twitter, Instagram, and other social media platforms at @StobiesGalaxy.
    0 Σχόλια 0 Μοιράστηκε
  • The art of two Mickeys

    Classic splitscreens, traditional face replacements and new approaches to machine learning-assisted face swapping allowed for twinning shots in ‘Mickey 17’. An excerpt from issue #32 of befores & afters magazine.
    The art of representing two characters on screen at the same time has become known as ‘twinning’. For Mickey 17 visual effects supervisor Dan Glass, the effect of seeing both Mickey 17 and 18 together was one he looked to achieve with a variety of methodologies. “With a technique like that,” he says, “you always want to use a range of tricks, because you don’t want people to figure it out. You want to keep them like, ‘Oh, wait a minute. How did they…?”
    “Going back to the way that Director Bong is so prepared and organized,” adds Glass, “it again makes the world of difference with that kind of work, because he thumbnails every shot. Then, some of them are a bit more fleshed out in storyboards. You can look at it and go, ‘Okay, in this situation, this is what the camera’s doing, this is what the actor’s doing,’ which in itself is quite interesting, because he pre-thinks all of this. You’d think that the actors show up and basically just have to follow the steps like robots. It’s not like that. He gives them an environment to work in, but the shots do end up extraordinarily close to what he thumbnails, and it made it a lot simpler to go through.”

    Those different approaches to twinning ranged from simple splitscreens, to traditional face replacements, and then substantially with a machine learned AI approach, now usually termed ‘face swapping’. What made the twinning work a tougher task than usual, suggests Glass, was the fact that the two Pattinson characters are virtually identical.
    “Normally, when you’re doing some kind of face replacement, you’re comparing it to a memory of the face. But this was right in front of you as two Mickeys looking strikingly similar.”
    Here’s how a typical twinning shot was achieved, as described by Glass. “Because Mickey was mostly dressed the same, with only a slight hair change, we were able to have Robert play both roles and to do them one after another. Sometimes, you have to do these things where hair and makeup or costume has a significant variation, so you’re either waiting a long time, which slows production, or you’re coming back at another time to do the different roles, which always makes the process a lot more complicated to match, but we were able to do that immediately.”

    “Based on the design of the shot,” continues Glass, “I would recommend which of Robert’s parts should be shot first. This was most often determined by which role had more impact on the camera movement. A huge credit goes to Robert for his ability to flip between the roles so effortlessly.”
    In the film, Mickey 17 is more passive and Mickey 18 is more aggressive. Pattinson reflected the distinct characters in his actions, including for a moment in which they fight. This fight, overseen by stunt coordinator Paul Lowe, represented moments of close interaction between the two Mickeys. It was here that a body double was crucial in shooting. The body double was also relied upon for the classic twinning technique of shooting ‘dirty’ over-the- shoulder out of focus shots of the double—ie. 17 looking at 18. However, it was quickly determined that even these would need face replacement work. “Robert’s jawline is so distinct that even those had to be replaced or shot as split screens,” observes Glass.

    When the shot was a moving one, no motion control was employed. “I’ve never been a big advocate for motion control,” states Glass. “To me it’s applicable when you’re doing things like miniatures where you need many matching passes, but I think when performances are involved, it interferes too much. It slows down a production’s speed of movement, but it’s also restrictive. Performance and camera always benefit from more flexibility.”
    “It helped tremendously that Director Bong and DOP Darius Khondji shot quite classically with minimal crane and Steadicam moves,” says Glass. “So, a lot of the moves are pan and dolly. There are some Steadicams in there that we were sometimes able to do splitscreens on. I wasn’t always sure that we could get away with the splitscreen as we shot it, but since we were always shooting the two roles, we had the footage to assess the practicality later. We were always prepared to go down a CG or machine learning route, but where we could use the splitscreen, that was the preference.”
    The Hydralite rig, developed by Volucap. Source:
    Rising Sun Pictureshandled the majority of twinning visual effects, completing them as splitscreen composites, 2D face replacements, and most notably via their machine learning toolset REVIZE, which utilized facial and body capture of Pattinson to train a model of his face and torso to swap for the double’s. A custom capture rig, dubbed the ‘Crazy Rig’ and now officially, The Hydralite, was devised and configured by Volucap to capture multiple angles of Robert on set in each lighting environment in order to produce the best possible reference for the machine learning algorithm. “For me, it was a completely legitimate use of the technique,” attests Glass, in terms of the machine learning approach. “All of the footage that we used to go into that process was captured on our movie for our movie. There’s nothing historic, or going through past libraries of footage, and it was all with Robert’s approval. I think the results were tremendous.”
    “It’s staggering to me as I watch the movie that the performances of each character are so flawlessly consistent throughout the film, because I know how much we were jumping around,” notes Glass. “I did encourage that we rehearse scenes ahead. Let’s say 17 was going to be the first role we captured, I’d have them rehearse it the other way around so that the double knew what he was going to do. Therefore, eyelines, movement, pacing and in instances where we were basically replacing the likeness of his head or even torso, we were still able to use the double’s performance and then map to that.”

    Read the full Mickey 17 issue of befores & afters magazine in PRINT from Amazon or as a DIGITAL EDITION on Patreon. Remember, you can also subscribe to the DIGITAL EDITION as a tier on the Patreon and get a new issue every time one is released.
    The post The art of two Mickeys appeared first on befores & afters.
    #art #two #mickeys
    The art of two Mickeys
    Classic splitscreens, traditional face replacements and new approaches to machine learning-assisted face swapping allowed for twinning shots in ‘Mickey 17’. An excerpt from issue #32 of befores & afters magazine. The art of representing two characters on screen at the same time has become known as ‘twinning’. For Mickey 17 visual effects supervisor Dan Glass, the effect of seeing both Mickey 17 and 18 together was one he looked to achieve with a variety of methodologies. “With a technique like that,” he says, “you always want to use a range of tricks, because you don’t want people to figure it out. You want to keep them like, ‘Oh, wait a minute. How did they…?” “Going back to the way that Director Bong is so prepared and organized,” adds Glass, “it again makes the world of difference with that kind of work, because he thumbnails every shot. Then, some of them are a bit more fleshed out in storyboards. You can look at it and go, ‘Okay, in this situation, this is what the camera’s doing, this is what the actor’s doing,’ which in itself is quite interesting, because he pre-thinks all of this. You’d think that the actors show up and basically just have to follow the steps like robots. It’s not like that. He gives them an environment to work in, but the shots do end up extraordinarily close to what he thumbnails, and it made it a lot simpler to go through.” Those different approaches to twinning ranged from simple splitscreens, to traditional face replacements, and then substantially with a machine learned AI approach, now usually termed ‘face swapping’. What made the twinning work a tougher task than usual, suggests Glass, was the fact that the two Pattinson characters are virtually identical. “Normally, when you’re doing some kind of face replacement, you’re comparing it to a memory of the face. But this was right in front of you as two Mickeys looking strikingly similar.” Here’s how a typical twinning shot was achieved, as described by Glass. “Because Mickey was mostly dressed the same, with only a slight hair change, we were able to have Robert play both roles and to do them one after another. Sometimes, you have to do these things where hair and makeup or costume has a significant variation, so you’re either waiting a long time, which slows production, or you’re coming back at another time to do the different roles, which always makes the process a lot more complicated to match, but we were able to do that immediately.” “Based on the design of the shot,” continues Glass, “I would recommend which of Robert’s parts should be shot first. This was most often determined by which role had more impact on the camera movement. A huge credit goes to Robert for his ability to flip between the roles so effortlessly.” In the film, Mickey 17 is more passive and Mickey 18 is more aggressive. Pattinson reflected the distinct characters in his actions, including for a moment in which they fight. This fight, overseen by stunt coordinator Paul Lowe, represented moments of close interaction between the two Mickeys. It was here that a body double was crucial in shooting. The body double was also relied upon for the classic twinning technique of shooting ‘dirty’ over-the- shoulder out of focus shots of the double—ie. 17 looking at 18. However, it was quickly determined that even these would need face replacement work. “Robert’s jawline is so distinct that even those had to be replaced or shot as split screens,” observes Glass. When the shot was a moving one, no motion control was employed. “I’ve never been a big advocate for motion control,” states Glass. “To me it’s applicable when you’re doing things like miniatures where you need many matching passes, but I think when performances are involved, it interferes too much. It slows down a production’s speed of movement, but it’s also restrictive. Performance and camera always benefit from more flexibility.” “It helped tremendously that Director Bong and DOP Darius Khondji shot quite classically with minimal crane and Steadicam moves,” says Glass. “So, a lot of the moves are pan and dolly. There are some Steadicams in there that we were sometimes able to do splitscreens on. I wasn’t always sure that we could get away with the splitscreen as we shot it, but since we were always shooting the two roles, we had the footage to assess the practicality later. We were always prepared to go down a CG or machine learning route, but where we could use the splitscreen, that was the preference.” The Hydralite rig, developed by Volucap. Source: Rising Sun Pictureshandled the majority of twinning visual effects, completing them as splitscreen composites, 2D face replacements, and most notably via their machine learning toolset REVIZE, which utilized facial and body capture of Pattinson to train a model of his face and torso to swap for the double’s. A custom capture rig, dubbed the ‘Crazy Rig’ and now officially, The Hydralite, was devised and configured by Volucap to capture multiple angles of Robert on set in each lighting environment in order to produce the best possible reference for the machine learning algorithm. “For me, it was a completely legitimate use of the technique,” attests Glass, in terms of the machine learning approach. “All of the footage that we used to go into that process was captured on our movie for our movie. There’s nothing historic, or going through past libraries of footage, and it was all with Robert’s approval. I think the results were tremendous.” “It’s staggering to me as I watch the movie that the performances of each character are so flawlessly consistent throughout the film, because I know how much we were jumping around,” notes Glass. “I did encourage that we rehearse scenes ahead. Let’s say 17 was going to be the first role we captured, I’d have them rehearse it the other way around so that the double knew what he was going to do. Therefore, eyelines, movement, pacing and in instances where we were basically replacing the likeness of his head or even torso, we were still able to use the double’s performance and then map to that.” Read the full Mickey 17 issue of befores & afters magazine in PRINT from Amazon or as a DIGITAL EDITION on Patreon. Remember, you can also subscribe to the DIGITAL EDITION as a tier on the Patreon and get a new issue every time one is released. The post The art of two Mickeys appeared first on befores & afters. #art #two #mickeys
    BEFORESANDAFTERS.COM
    The art of two Mickeys
    Classic splitscreens, traditional face replacements and new approaches to machine learning-assisted face swapping allowed for twinning shots in ‘Mickey 17’. An excerpt from issue #32 of befores & afters magazine. The art of representing two characters on screen at the same time has become known as ‘twinning’. For Mickey 17 visual effects supervisor Dan Glass, the effect of seeing both Mickey 17 and 18 together was one he looked to achieve with a variety of methodologies. “With a technique like that,” he says, “you always want to use a range of tricks, because you don’t want people to figure it out. You want to keep them like, ‘Oh, wait a minute. How did they…?” “Going back to the way that Director Bong is so prepared and organized,” adds Glass, “it again makes the world of difference with that kind of work, because he thumbnails every shot. Then, some of them are a bit more fleshed out in storyboards. You can look at it and go, ‘Okay, in this situation, this is what the camera’s doing, this is what the actor’s doing,’ which in itself is quite interesting, because he pre-thinks all of this. You’d think that the actors show up and basically just have to follow the steps like robots. It’s not like that. He gives them an environment to work in, but the shots do end up extraordinarily close to what he thumbnails, and it made it a lot simpler to go through.” Those different approaches to twinning ranged from simple splitscreens, to traditional face replacements, and then substantially with a machine learned AI approach, now usually termed ‘face swapping’. What made the twinning work a tougher task than usual, suggests Glass, was the fact that the two Pattinson characters are virtually identical. “Normally, when you’re doing some kind of face replacement, you’re comparing it to a memory of the face. But this was right in front of you as two Mickeys looking strikingly similar.” Here’s how a typical twinning shot was achieved, as described by Glass. “Because Mickey was mostly dressed the same, with only a slight hair change, we were able to have Robert play both roles and to do them one after another. Sometimes, you have to do these things where hair and makeup or costume has a significant variation, so you’re either waiting a long time, which slows production, or you’re coming back at another time to do the different roles, which always makes the process a lot more complicated to match, but we were able to do that immediately.” “Based on the design of the shot,” continues Glass, “I would recommend which of Robert’s parts should be shot first. This was most often determined by which role had more impact on the camera movement. A huge credit goes to Robert for his ability to flip between the roles so effortlessly.” In the film, Mickey 17 is more passive and Mickey 18 is more aggressive. Pattinson reflected the distinct characters in his actions, including for a moment in which they fight. This fight, overseen by stunt coordinator Paul Lowe, represented moments of close interaction between the two Mickeys. It was here that a body double was crucial in shooting. The body double was also relied upon for the classic twinning technique of shooting ‘dirty’ over-the- shoulder out of focus shots of the double—ie. 17 looking at 18. However, it was quickly determined that even these would need face replacement work. “Robert’s jawline is so distinct that even those had to be replaced or shot as split screens,” observes Glass. When the shot was a moving one, no motion control was employed. “I’ve never been a big advocate for motion control,” states Glass. “To me it’s applicable when you’re doing things like miniatures where you need many matching passes, but I think when performances are involved, it interferes too much. It slows down a production’s speed of movement, but it’s also restrictive. Performance and camera always benefit from more flexibility.” “It helped tremendously that Director Bong and DOP Darius Khondji shot quite classically with minimal crane and Steadicam moves,” says Glass. “So, a lot of the moves are pan and dolly. There are some Steadicams in there that we were sometimes able to do splitscreens on. I wasn’t always sure that we could get away with the splitscreen as we shot it, but since we were always shooting the two roles, we had the footage to assess the practicality later. We were always prepared to go down a CG or machine learning route, but where we could use the splitscreen, that was the preference.” The Hydralite rig, developed by Volucap. Source: https://volucap.com Rising Sun Pictures (visual effects supervisor Guido Wolter) handled the majority of twinning visual effects, completing them as splitscreen composites, 2D face replacements, and most notably via their machine learning toolset REVIZE, which utilized facial and body capture of Pattinson to train a model of his face and torso to swap for the double’s. A custom capture rig, dubbed the ‘Crazy Rig’ and now officially, The Hydralite, was devised and configured by Volucap to capture multiple angles of Robert on set in each lighting environment in order to produce the best possible reference for the machine learning algorithm. “For me, it was a completely legitimate use of the technique,” attests Glass, in terms of the machine learning approach. “All of the footage that we used to go into that process was captured on our movie for our movie. There’s nothing historic, or going through past libraries of footage, and it was all with Robert’s approval. I think the results were tremendous.” “It’s staggering to me as I watch the movie that the performances of each character are so flawlessly consistent throughout the film, because I know how much we were jumping around,” notes Glass. “I did encourage that we rehearse scenes ahead. Let’s say 17 was going to be the first role we captured, I’d have them rehearse it the other way around so that the double knew what he was going to do. Therefore, eyelines, movement, pacing and in instances where we were basically replacing the likeness of his head or even torso, we were still able to use the double’s performance and then map to that.” Read the full Mickey 17 issue of befores & afters magazine in PRINT from Amazon or as a DIGITAL EDITION on Patreon. Remember, you can also subscribe to the DIGITAL EDITION as a tier on the Patreon and get a new issue every time one is released. The post The art of two Mickeys appeared first on befores & afters.
    0 Σχόλια 0 Μοιράστηκε