--- In the dim corners of virtual spaces, where anonymity cloaks desires, a phenomenon unfolds nightly—VRChat porn. This intricate dance between role-play and community-driven NSFW content has birthed a realm pulsating with intensity and longing. Here, avatars come alive, each movement a brushstroke on the canvas of fantasy, where the boundaries of reality blur into obscurity. ## The Allure...

road bikes, luxury bicycles, 3D printing, J.Laverack, Aston Martin, titanium bicycles, high-quality cycling, innovative design ## Introduction In the world of cycling, a new revolution is brewing, one that combines cutting-edge technology with the elegance of luxury design. The collaboration between British company J.Laverack and the renowned luxury sports car manufacturer Aston Martin has...

Science & technology | Hidden in plain sightA routine test for fetal abnormalities could improve a mother’s healthStudies show these can help detect pre-eclampsia and predict preterm births Illustration: Anna Kövecses Jun 11th 2025WHEN NON-INVASIVE prenatal testing (NIPT) arrived in 2011, it transformed pregnancy. With a simple blood test, scientists could now sweep a mother’s bloodstream for scraps of placental DNA, uncovering fetal genetic defects and shedding light on the health of the unborn baby. But the potential to monitor the mother’s health went largely unappreciated.Explore moreThis article appeared in the Science & technology section of the print edition under the headline “Testing time”From the June 14th 2025 editionDiscover stories from this section and more in the list of contents⇒Explore the editionReuse this content

Perhaps the oldest, most pernicious form of human bias is that of men toward women. It often started at the moment of birth. In ancient Athens, at a public ceremony called the amphidromia, fathers would inspect a newborn and decide whether it would be part of the family, or be cast away. One often socially acceptable reason for abandoning the baby: It was a girl. Female infanticide has been distressingly common in many societies — and its practice is not just ancient history. In 1990, the Nobel Prize-winning economist Amartya Sen looked at birth ratios in Asia, North Africa, and China and calculated that more than 100 million women were essentially “missing” — meaning that, based on the normal ratio of boys to girls at birth and the longevity of both genders, there was a huge missing number of girls who should have been born, but weren’t. Sen’s estimate came before the truly widespread adoption of ultrasound tests that could determine the sex of a fetus in utero — which actually made the problem worse, leading to a wave of sex-selective abortions. These were especially common in countries like India and China; the latter’s one-child policy and old biases made families desperate for their one child to be a boy. The Economist has estimated that since 1980 alone, there have been approximately 50 million fewer girls born worldwide than would naturally be expected, which almost certainly means that roughly that nearly all of those girls were aborted for no other reason than their sex. The preference for boys was a bias that killed in mass numbers.But in one of the most important social shifts of our time, that bias is changing. In a great cover story earlier this month, The Economist reported that the number of annual excess male births has fallen from a peak of 1.7 million in 2000 to around 200,000, which puts it back within the biologically standard birth ratio of 105 boys for every 100 girls. Countries that once had highly skewed sex ratios — like South Korea, which saw almost 116 boys born for every 100 girls in 1990 — now have normal or near-normal ratios. Altogether, The Economist estimated that the decline in sex preference at birth in the past 25 years has saved the equivalent of 7 million girls. That’s comparable to the number of lives saved by anti-smoking efforts in the US. So how, exactly, have we overcome a prejudice that seemed so embedded in human society?Success in school and the workplaceFor one, we have relaxed discrimination against girls and women in other ways — in school and in the workplace. With fewer limits, girls are outperforming boys in the classroom. In the most recent international PISA tests, considered the gold standard for evaluating student performance around the world, 15-year-old girls beat their male counterparts in reading in 79 out of 81 participating countries or economies, while the historic male advantage in math scores has fallen to single digits. Girls are also dominating in higher education, with 113 female students at that level for every 100 male students. While women continue to earn less than men, the gender pay gap has been shrinking, and in a number of urban areas in the US, young women have actually been outearning young men. Government policies have helped accelerate that shift, in part because they have come to recognize the serious social problems that eventually result from decades of anti-girl discrimination. In countries like South Korea and China, which have long had some of the most skewed gender ratios at birth, governments have cracked down on technologies that enable sex-selective abortion. In India, where female infanticide and neglect have been particularly horrific, slogans like “Save the Daughter, Educate the Daughter” have helped change opinions. A changing preferenceThe shift is being seen not just in birth sex ratios, but in opinion polls — and in the actions of would-be parents.Between 1983 and 2003, The Economist reported, the proportion of South Korean women who said it was “necessary” to have a son fell from 48 percent to 6 percent, while nearly half of women now say they want daughters. In Japan, the shift has gone even further — as far back as 2002, 75 percent of couples who wanted only one child said they hoped for a daughter.In the US, which allows sex selection for couples doing in-vitro fertilization, there is growing evidence that would-be parents prefer girls, as do potential adoptive parents. While in the past, parents who had a girl first were more likely to keep trying to have children in an effort to have a boy, the opposite is now true — couples who have a girl first are less likely to keep trying. A more equal futureThere’s still more progress to be made. In northwest of India, for instance, birth ratios that overly skew toward boys are still the norm. In regions of sub-Saharan Africa, birth sex ratios may be relatively normal, but post-birth discrimination in the form of poorer nutrition and worse medical care still lingers. And course, women around the world are still subject to unacceptable levels of violence and discrimination from men.And some of the reasons for this shift may not be as high-minded as we’d like to think. Boys around the world are struggling in the modern era. They increasingly underperform in education, are more likely to be involved in violent crime, and in general, are failing to launch into adulthood. In the US, 20 percent of American men between 25 and 34 still live with their parents, compared to 15 percent of similarly aged women. It also seems to be the case that at least some of the increasing preference for girls is rooted in sexist stereotypes. Parents around the world may now prefer girls partly because they see them as more likely to take care of them in their old age — meaning a different kind of bias against women, that they are more natural caretakers, may be paradoxically driving the decline in prejudice against girls at birth.But make no mistake — the decline of boy preference is a clear mark of social progress, one measured in millions of girls’ lives saved. And maybe one Father’s Day, not too long from now, we’ll reach the point where daughters and sons are simply children: equally loved and equally welcomed.A version of this story originally appeared in the Good News newsletter. Sign up here!See More:

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.

The roster of skaters originally featured in Tony Hawk’s™ Pro Skater™ 3 and Tony Hawk’s™ Pro Skater™ 4 helped to further catapult skateboarding culture into the mainstream as big names like Bob Burnquist, Steve Caballero, Elissa Steamer, and Chad Muska joined Tony Hawk in a stacked roster of award-winning pro skaters capable of shredding in and out of the game. In this feature, following the Demo announcement and the full soundtrack reveal, we’re proud to share the full roster of returning skaters in the upcoming Tony Hawk’s™ Pro Skater™ 3 + 4arriving on PlayStation 4 and 5, Xbox Series X|S, Xbox One, Nintendo Switch, Nintendo Switch 2, and PC (Battle.net, Steam, Microsoft PC Store). Tony Hawk’s Pro Skater 3 + 4 launches on July 11. THPS 3 + 4: Returning Skaters From gold medalists to progenitors of some of today’s most iconic skateboarding tricks, these classic skaters were instrumental in bringing skateboarding culture to a wider audience. Mixing courage, creativity, and an iron will, they’re more than ready to tackle any obstacle put before them. “Being in the original games was epic!” shares Elissa Steamer, who was the first playable female skater in the original Tony Hawk’s Pro Skater game. “It was semi-life changing. I can’t say enough about how stoked I was – and am now! – to be in the games.” “From the moment Tony asked, it was an honor, yet I had no idea of what it would come to mean,” says Rodney Mullen, originator of the kickflip and largely considered one of the most influential skaters in the sport. “The first time I showed up on tour after the release of the game, I recall ‘em shop owners having to put me on top of the tour van roof to manage so that I could sign things in all the madness. The crowd was rocking the van back and forth! [It] blew my mind, the impact it had.” “The game attracted such a broader group of skaters, which has elevated our community in layered ways: from tricks to societal acceptance to the respect we get from people who often thought otherwise, like parents discouraging their kids who were simply outsiders looking for a place to belong,” Mullen continues. “Skating is integrated with a culture, a way of being, more than pretty much any other sport I can think of. The way Tony’s game shows that via the music, art, and vibe batted this home. It’s cool to be understood.”  When Tony Hawk’s Pro Skater 3 + 4 launches this July, here are the returning skaters ready to hit the pavement once again, including skaters featured in the original Tony Hawk’s Pro Skater 3 and Tony Hawk’s Pro Skater 4 games plus other titles in the series. Tony Hawk San Diego, California Style: Vert / Stance: Goofy Tony Hawk made history by landing the first ever 900 at the 1999 X Games, skyrocketing the sport into the mainstream. Today he remains the sport’s most iconic figure. Bob Burnquist Rio de Janeiro, Brazil Style: Vert / Stance: Regular Bob Burnquist shocked the skateboarding world when he landed the first Fakie 900. His iconic “Dreamland” skatepark is home to a permanent Mega Ramp. Bucky Lasek Baltimore, Maryland Style: Vert / Stance: Regular Known for his vert skills, Bucky has won 10 gold medals at the X Games and is one of only two vert skateboarders to have won three gold medals consecutively. Steve Caballero San Jose, California Style: Vert / Stance: Goofy An iconic skateboarder responsible for inventing various vert tricks. He holds the record for the highest air ever achieved on a halfpipe. Kareem Campbell Harlem, New York Style: Street / Stance: Regular Called the godfather of smooth street style, Kareem left his mark by popularizing the skateboard trick, “The Ghetto Bird,” and founded City Stars Skateboards. Geoff Rowley Liverpool, England Style: Street / Stance: Regular Geoff Joseph Rowley Jr. is an English skateboarder and owner of Civilware Service Corporation. In 2000 he was crowned “Skater of the Year” by Thrasher Magazine. Andrew Reynolds North Hollywood, California Style: Street / Stance: Regular Co-founder and owner of Baker Skateboards, Andrew Reynolds turned pro in 1995 and won Thrasher Magazine’s “Skater of the Year” award just three years later. Elissa Steamer San Francisco, California Style: Street / Stance: Regular Elissa is a four-time X Games gold medalist, the first female skateboarder to go pro, and the first woman ever inducted into the Skateboarding Hall of Fame. Chad Muska Los Angeles, California Style: Street / Stance: Regular Artist, musician, and entrepreneur. Described by the Transworld Skateboarding editor-in-chief as “one of the most marketable pros skateboarding has ever seen.” Eric Koston Los Angeles, California Style: Street / Stance: Goofy Co-founder of Fourstar Clothing and the skate brand The Berrics, Eric is a master of street skateboarding and a two-time X Games gold medalist. Rodney Mullen Gainesville, Florida Style: Freestyle / Stance: Regular One of the most influential skateboarders of all time, Rodney Mullen is the progenitor of the Flatground Ollie, Kickflip, Heelflip, and dozens of other iconic tricks. Jamie Thomas Dothan, Alabama Style: Street / Stance: Regular Nicknamed “The Chief,” Jamie is the owner and founder of Zero Skateboards. He helped film 1996’s “Welcome to Hell,” one of the most iconic skate videos ever made. Rune Glifberg Copenhagen, Denmark Style: Vert / Stance: Regular Nicknamed “The Danish Destroyer,” Rune Glifberg is one of three skaters to have competed at every X Games, amassing over 12 medals at the competition. Aori Nishimura Tokyo, Japan Style: Street / Stance: Regular Born in Edogawa, Tokyo in Japan, Aori Nishimura started skateboarding at the age of 7 and went on to become the first athlete from Japan to win gold at the X Games. Leo Baker Brooklyn, New York Style: Street / Stance: Goofy Leo is the first non-binary and transgender professional skateboarder in the Pro Skater™ series and has won three gold medals, placing in over 32 competitions.  Leticia Bufoni São Paulo, Brazil Style: Street / Stance: Goofy Multiple world record holder and six-time gold medalist. Named the #1 women’s street skateboarder by World Cup of Skateboarding four years in a row. Lizzie Armanto Santa Monica, California Style: Park / Stance: Regular A member of the Birdhouse skate team, Lizzie has amassed over 30 skateboarding awards and was the first female skater to complete “The Loop,” a 360-degree ramp. Nyjah Huston Laguna Beach, California Style: Street / Stance: Goofy One of skateboarding’s biggest stars, Nyjah has earned over 12 X Games gold medals, 6 Championship titles, and a bronze medal at the 2024 Summer of Olympics. Riley Hawk San Diego, California Style: Street / Stance: Goofy Riley Hawk decided to turn pro on his 21st birthday and became Skateboarder Magazine’s 2013 Amateur of the Year later that same day. Shane O’Neill Melbourne, Australia Style: Street / Stance: Goofy Australian skateboarder who is one of only a few skateboarders to win gold in all four major skateboarding contests, including the X Games and SLS. Tyshawn Jones Bronx, New York Style: Street / Stance: Regular A New York City native and two-time Thrasher Magazine “Skate of the Year” winner, Tyshawn Jones is the youngest skateboarder to ever achieve that accolade. The above skaters are far from the only icons you’ll encounter in the game’s large roster. Keep your eyes on the Tony Hawk’s Pro Skater blog found here for more info on Tony Hawk’s Pro Skater 3 + 4 as we approach its July 11 release date, including the full reveal of new skaters joining in on the fun.  Tony Hawk’s Pro Skater 3 + 4 rebuilds the original games from the ground up with classic and new skaters, parks, tricks, tracks, and more. Skate through a robust Career mode taking on challenges across two tours, chase high scores in Single Sessions and Speedruns, or go at your own pace in Free Skate. Get original with enhanced creation tools, go big in New Game+, and skate with your friends in cross-platform online multiplayer* supporting up to eight skaters at a time. New to the series? Hit up the in-game tutorial led by Tony Hawk himself to kick off your skating journey with tips on Ollies, kick flips, vert tricks, reverts, manuals, special tricks, and more. Don’t miss the Foundry Demo, available now, featuring playable skaters, two parks, and a selection of songs from the soundtrack. Pre-order Tony Hawk’s Pro Skater 3 + 4 on select platforms* for access to the demo and find more info here. Purchase the Digital Deluxe Edition and gain Early Access*** to play Tony Hawk’s™ Pro Skater™ 3 + 4 three days before the official July 11 launch date. Shred the parks and spread fear as the Doom Slayer and Revenant skaters plus get extra music, skate decks, and Create-A-Skater gear: Doom Slayer: Play as Doom Slayer, featuring a Standard and Retro outfit plus two unique special tricks and the Unmaykr Hoverboard. Revenant: Get evil with the Revenant, including two unique special tricks. Additional Music: Headbang to a selection of classic and modern music tracks added to the in-game soundtrack. Skate Decks: Access additional skate decks including Doom Slayer and Revenant themed designs. Create-A-Skater Items: Kit out your skater with additional apparel items. Pre-orders are now available for Tony Hawk’s Pro Skater 3 + 4 on PlayStation 4 and 5, Xbox Series X|S, Xbox One, Nintendo Switch, and PC. For more information, visit tonyhawkthegame.com. * Activision account and internet required for online multiplayer and other features. Platform gaming subscription may be required for multiplayer and other features (sold separately). **Foundry demo available on PlayStation 4 and 5, Xbox Series X|S, Xbox One, and PC. Not available on Nintendo Switch. Foundry Demo availability and launch date(s) subject to change. Internet connection required. *** Actual play time subject to possible outages and applicable time zone differences.

We did it gang. We completed another week in the impossible survival sim that is real life. Give yourself a appreciative pat on the back and gaze wistfully towards whatever adventures or blissful respite the weekend might bring.This week I've mostly been recovering from my birthday celebrations, which entailed a bountiful Korean Barbecue that left me with a rampant case of the meat sweats and a pub crawl around one of Manchester's finest suburbs. There was no time for video games, but that's not always a bad thing. Distance makes the heart grow fonder, after all.I was welcomed back to the imaginary office with a news bludgeon to the face. The headlines this week have come thick and fast, bringing hardware announcements, more layoffs, and some notable sales milestones. As always, there's a lot to digest, so let's venture once more into the fray. The first Xbox handhelds have finally arrivedvia Game Developer // Microsoft finally stopped flirting with the idea of launching a handheld this week and unveiled not one, but two devices called the ROG Xbox Ally and ROG Xbox Ally X. The former is pitched towards casual players, while the latter aims to entice hardcore video game aficionados. Both devices were designed in collaboration with Asus and will presumably retail at price points that reflect their respective innards. We don't actually know yet, mind, because Microsoft didn't actually state how much they'll cost. You have the feel that's where the company really needs to stick the landing here.Related:Switch 2 tops 3.5 million sales to deliver Nintendo's biggest console launchvia Game Developer // Four days. That's all it took for the Switch 2 to shift over 3.5 million units worldwide to deliver Nintendo's biggest console launch ever. The original Switch needed a month to reach 2.74 million sales by contrast, while the PS5 needed two months to sell 4.5 million units worldwide. Xbox sales remain a mystery because Microsoft just doesn't talk about that sort of thing anymore, which is decidedly frustrating for those oddballs (read: this writer) who actually enjoy sifting through financial documents in search of those juicy juicy numbers.Inside the ‘Dragon Age’ Debacle That Gutted EA’s BioWare Studiovia Bloomberg (paywalled) // How do you kill a franchise like Dragon Age and leave a studio with the pedigree of BioWare in turmoil? According to a new report from Bloomberg, the answer will likely resonate with developers across the industry: corporate meddling. Sources speaking to the publication explained how Dragon Age: The Veilguard, which failed to meet the expectations of parent company EA, was in constant disarray because the American publisher couldn't decide whether it should be a live-service or single player title. Indecision from leadership within EA and an eventual pivot away from the live-service model only caused more confusion, with BioWare being told to implement foundational changes within impossible timelines. It's a story that's all the more alarming because of how familiar it feels.Related:Sony is making layoffs at Days Gone developer Bend Studiovia Game Developer // Sony has continued its Tony Award-winning tun as the Grim Reaper by cutting even more jobs within PlayStation Studios. Days Gone developer Bend Studio was the latest casualty, with the first-party developer confirming a number of employees were laid off just months after the cancellation of a live-service project. Sony didn't confirm how many people lost their jobs, but Bloomberg reporter Jason Schreier heard that around 40 people (roughly 30 percent of the studio's headcount) were let go. Embracer CEO Lars Wingefors to become executive chair and focus on M&Avia Game Developer // Somewhere, in a deep dark corner of the world, the monkey's paw has curled. Embracer CEO Lars Wingefors, who demonstrated his leadership nous by spending years embarking on a colossal merger and acquisition spree only to immediately start downsizing, has announced he'll be stepping down as CEO. The catch? Wingefors is currently proposed to be appointed executive chair of the board of Embracer. In his new role, he'll apparently focus on strategic initiatives, capital allocation, and mergers and acquisitions. And people wonder why satire is dead. Related:Hong Kong Outlaws a Video Game, Saying It Promotes 'Armed Revolution'via The New York Times (paywalled) // National security police in Hong Kong have banned a Taiwanese video game called Reversed Front: Bonfire for supposedly "advocating armed revolution." Authorities in the region warned that anybody who downloads or recommends the online strategy title will face serious legal charges. The game has been pulled from Apple's marketplace in Hong Kong but is still available for download elsewhere. It was never available in mainland China. Developer ESC Taiwan, part of an group of volunteers who are vocal detractors of China's Communist Party, thanked Hong Kong authorities for the free publicity in a social media post and said the ban shows how political censorship remains prominent in the territory. RuneScape developer accused of ‘catering to American conservatism’ by rolling back Pride Month eventsvia PinkNews // Runescape developers inside Jagex have reportedly been left reeling after the studio decided to pivot away from Pride Month content to focus more on "what players wanted." Jagex CEO broke the news to staff with a post on an internal message board, prompting a rush of complaints—with many workers explaining the content was either already complete or easy to implement. Though Jagex is based in the UK, it's parent company CVC Capital Partners operates multiple companies in the United States. It's a situation that left one employee who spoke to PinkNews questioning whether the studio has caved to "American conservatism." SAG-AFTRA suspends strike and instructs union members to return to workvia Game Developer // It has taken almost a year, but performer union SAG-AFTRA has finally suspended strike action and instructed members to return to work. The decision comes after protracted negotiations with major studios who employ performers under the Interactive Media Agreement. SAG-AFTRA had been striking to secure better working conditions and AI protections for its members, and feels it has now secured a deal that will install vital "AI guardrails."A Switch 2 exclusive Splatoon spinoff was just shadow-announced on Nintendo Todayvia Game Developer // Nintendo did something peculiar this week when it unveiled a Splatoon spinoff out of the blue. That in itself might not sound too strange, but for a short window the announcement was only accessible via the company's new Nintendo Today mobile app. It's a situation that left people without access to the app questioning whether the news was even real. Nintendo Today prevented users from capturing screenshots or footage, only adding to the sense of confusion. It led to this reporter branding the move a "shadow announcement," which in turn left some of our readers perplexed. Can you ever announce and announcement? What does that term even mean? Food for thought. A wonderful new Big Walk trailer melted this reporter's heartvia House House (YouTube) //  The mad lads behind Untitled Goose Game are back with a new jaunt called Big Walk. This one has been on my radar for a while, but the studio finally debuted a gameplay overview during Summer Game Fest and it looks extraordinary in its purity. It's about walking and talking—and therein lies the charm. Players are forced to cooperate to navigate a lush open world, solve puzzles, and embark upon hijinks. Proximity-based communication is the core mechanic in Big Walk—whether that takes the form of voice chat, written text, hand signals, blazing flares, or pictograms—and it looks like it'll lead to all sorts of weird and wonderful antics. It's a pitch that cuts through because it's so unashamedly different, and there's a lot to love about that. I'm looking forward to this one.

“Wait, can users actually add products to the cart?”Every prototype faces that question or one like it. You start to explain it’s “just Figma,” “just dummy data,” but what if you didn’t need disclaimers?What if you could hand clients—or your team—a working, data-connected mock-up of their website, or new pages and components, in less time than it takes to wireframe?That’s the challenge we’ll tackle today. But first, we need to look at:The problem with today’s prototyping toolsPick two: speed, flexibility, or interactivity.The prototyping ecosystem, despite having amazing software that addresses a huge variety of needs, doesn’t really have one tool that gives you all three.Wireframing apps let you draw boxes in minutes but every button is fake. Drag-and-drop builders animate scroll triggers until you ask for anything off-template. Custom code frees you… after you wave goodbye to a few afternoons.AI tools haven’t smashed the trade-off; they’ve just dressed it in flashier costumes. One prompt births a landing page, the next dumps a 2,000-line, worse-than-junior-level React file in your lap. The bottleneck is still there. Builder’s approach to website mockupsWe’ve been trying something a little different to maintain speed, flexibility, and interactivity while mocking full websites. Our AI-driven visual editor:Spins up a repo in seconds or connects to your existing one to use the code as design inspiration. React, Vue, Angular, and Svelte all work out of the box. Lets you shape components via plain English, visual edits, copy/pasted Figma frames, web inspos, MCP tools, and constant visual awareness of your entire website. Commits each change as a clean GitHub pull request your team can review like hand-written code. All your usual CI checks and lint rules apply.And if you need a tweak, you can comment to @builderio-bot right in the GitHub PR to make asynchronous changes without context switching.This results in a live site the café owner can interact with today, and a branch your devs can merge tomorrow. Stakeholders get to click actual buttons and trigger real state—no more “so, just imagine this works” demos.Let’s see it in action.From blank canvas to working mockup in five promptsToday, I’m going to mock up a fake business website. You’re welcome to create a real one.Before we fire off a single prompt, grab a note and write:Business name & vibe Core pages Primary goal Brand palette & toneThat’s it. Don’t sweat the details—we can always iterate. For mine, I wrote:1. Sunny Trails Bakery — family-owned, feel-good, smells like warm cinnamon. 2. Home, About, Pricing / Subscription Box, Menu (with daily specials). 3. Drive online orders and foot traffic—every CTA should funnel toward “Order Now” or “Reserve a Table.” 4. Warm yellow, chocolate brown, rounded typography, playful copy.We’re not trying to fit everything here. What matters is clarity on what we’re creating, so the AI has enough context to produce usable scaffolds, and so later tweaks stay aligned with the client’s vision. Builder will default to using React, Vite, and Tailwind. If you want a different JS framework, you can link an existing repo in that stack. In the near future, you won’t need to do this extra step to get non-React frameworks to function.(Free tier Builder gives you 5 AI credits/day and 25/month—plenty to follow along with today’s demo. Upgrade only when you need it.)An entire website from the first promptNow, we’re ready to get going.Head over to Builder.io and paste in this prompt or your own:Create a cozy bakery website called “Sunny Trails Bakery” with pages for: • Home • About • Pricing • Menu Brand palette: warm yellow and chocolate brown. Tone: playful, inviting. The restaurant is family-owned, feel-good, and smells like cinnamon. The goal of this site is to drive online orders and foot traffic—every CTA should funnel toward "Order Now" or "Reserve a Table."Once you hit enter, Builder will spin up a new dev container, and then inside that container, the AI will build out the first version of your site. You can leave the page and come back when it’s done.Now, before we go further, let’s create our repo, so that we get version history right from the outset. Click “Create Repo” up in the top right, and link your GitHub account.Once the process is complete, you’ll have a brand new repo.If you need any help on this step, or any of the below, check out these docs.Making the mockup’s order system workFrom our one-shot prompt, we’ve already got a really nice start for our client. However, when we press the “Order Now” button, we just get a generic alert. Let’s fix this.The best part about connecting to GitHub is that we get version control. Head back to your dashboard and edit the settings of your new project. We can give it a better name, and then, in the “Advanced” section, we can change the “Commit Mode” to “Pull Requests.”Now, we have the ability to create new branches right within Builder, allowing us to make drastic changes without worrying about the main version. This is also helpful if you’d like to show your client or team a few different versions of the same prototype.On a new branch, I’ll write another short prompt:Can you make the "Order Now" button work, even if it's just with dummy JSON for now?As you can see in the GIF above, Builder creates an ordering system and a fully mobile-responsive cart and checkout flow.Now, we can click “Send PR” in the top right, and we have an ordinary GitHub PR that can be reviewed and merged as needed.This is what’s possible in two prompts. For our third, let’s gussy up the style.If you’re like me, you might spend a lot of time admiring other people’s cool designs and learning how to code up similar components in your own style.Luckily, Builder has this capability, too, with our Chrome extension. I found a “Featured Posts” section on OpenAI’s website, where I like how the layout and scrolling work. We can copy and paste it onto our “Featured Treats” section, retaining our cafe’s distinctive brand style.Don’t worry—OpenAI doesn’t mind a little web scraping.You can do this with any component on any website, so your own projects can very quickly become a “best of the web” if you know what you’re doing.Plus, you can use Figma designs in much the same way, with even better design fidelity. Copy and paste a Figma frame with our Figma plugin, and tell the AI to either use the component as inspiration or as a 1:1 to reference for what the design should be.(You can grab our design-to-code guide for a lot more ideas of what this can help you accomplish.)Now, we’re ready to send our PR. This time, let’s take a closer look at the code the AI has created.As you can see, the code is neatly formatted into two reusable components. Scrolling down further, I find a CSS file and then the actual implementation on the homepage, with clean JSON to represent the dummy post data.Design tweaks to the mockup with visual editsOne issue that cropped up when the AI brought in the OpenAI layout is that it changed my text from “Featured Treats” to “Featured Stories & Treats.” I’ve realized I don’t like either, and I want to replace that text with: “Fresh Out of the Bakery.”It would be silly, though, to prompt the AI just for this small tweak. Let’s switch into edit mode.Edit Mode lets you select any component and change any of its content or underlying CSS directly. You get a host of Webflow-like options to choose from, so that you can finesse the details as needed.Once you’ve made all the visual changes you want—maybe tweaking a button color or a border radius—you can click “Apply Edits,” and the AI will ensure the underlying code matches your repo’s style.Async fixes to the mockup with Builder BotNow, our pull request is nearly ready to merge, but I found one issue with it:When we copied the OpenAI website layout earlier, one of the blog posts had a video as its featured graphic instead of just an image. This is cool for OpenAI, but for our bakery, I just wanted images in this section. Since I didn’t instruct Builder’s AI otherwise, it went ahead and followed the layout and created extra code for video capability.No problem. We can fix this inside GItHub with our final prompt. We just need to comment on the PR and tag builderio-bot. Within about a minute, Builder Bot has successfully removed the video functionality, leaving a minimal diff that affects only the code it needed to. For example: Returning to my project in Builder, I can see that the bot’s changes are accounted for in the chat window as well, and I can use the live preview link to make sure my site works as expected:Now, if this were a real project, you could easily deploy this to the web for your client. After all, you’ve got a whole GitHub repo. This isn’t just a mockup; it’s actual code you can tweak—with Builder or Cursor or by hand—until you’re satisfied to run the site in production.So, why use Builder to mock up your website?Sure, this has been a somewhat contrived example. A real prototype is going to look prettier, because I’m going to spend more time on pieces of the design that I don’t like as much.But that’s the point of the best AI tools: they don’t take you, the human, out of the loop.You still get to make all the executive decisions, and it respects your hard work. Since you can constantly see all the code the AI creates, work in branches, and prompt with component-level precision, you can stop worrying about AI overwriting your opinions and start using it more as the tool it’s designed to be.You can copy in your team’s Figma designs, import web inspos, connect MCP servers to get Jira tickets in hand, and—most importantly—work with existing repos full of existing styles that Builder will understand and match, just like it matched OpenAI’s layout to our little cafe.So, we get speed, flexibility, and interactivity all the way from prompt to PR to production.Try Builder today.

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]

Donald Trump’s military parade in Washington this weekend — a show of force in the capital that just happens to take place on the president’s birthday — smacks of authoritarian Dear Leader-style politics (even though Trump actually got the idea after attending the 2017 Bastille Day parade in Paris).Yet as disconcerting as the imagery of tanks rolling down Constitution Avenue will be, it’s not even close to Trump’s most insidious assault on the US military’s historic and democratically essential nonpartisan ethos.In fact, it’s not even the most worrying thing he’s done this week.On Tuesday, the president gave a speech at Fort Bragg, an Army base home to Special Operations Command. While presidential speeches to soldiers are not uncommon — rows of uniformed troops make a great backdrop for a foreign policy speech — they generally avoid overt partisan attacks and campaign-style rhetoric. The soldiers, for their part, are expected to be studiously neutral, laughing at jokes and such, but remaining fully impassive during any policy conversation.That’s not what happened at Fort Bragg. Trump’s speech was a partisan tirade that targeted “radical left” opponents ranging from Joe Biden to Los Angeles Mayor Karen Bass. He celebrated his deployment of Marines to Los Angeles, proposed jailing people for burning the American flag, and called on soldiers to be “aggressive” toward the protesters they encountered.The soldiers, for their part, cheered Trump and booed his enemies — as they were seemingly expected to. Reporters at Military.com, a military news service, uncovered internal communications from 82nd Airborne leadership suggesting that the crowd was screened for their political opinions.“If soldiers have political views that are in opposition to the current administration and they don’t want to be in the audience then they need to speak with their leadership and get swapped out,” one note read.To call this unusual is an understatement. I spoke with four different experts on civil-military relations, two of whom teach at the Naval War College, about the speech and its implications. To a person, they said it was a step towards politicizing the military with no real precedent in modern American history.“That is, I think, a really big red flag because it means the military’s professional ethic is breaking down internally,” says Risa Brooks, a professor at Marquette University. “Its capacity to maintain that firewall against civilian politicization may be faltering.”This may sound alarmist — like an overreading of a one-off incident — but it’s part of a bigger pattern. The totality of Trump administration policies, ranging from the parade in Washington to the LA troop deployment to Secretary of Defense Pete Hegseth’s firing of high-ranking women and officers of color, suggests a concerted effort to erode the military’s professional ethos and turn it into an institution subservient to the Trump administration’s whims. This is a signal policy aim of would-be dictators, who wish to head off the risk of a coup and ensure the armed forces’ political reliability if they are needed to repress dissent in a crisis.Steve Saideman, a professor at Carleton University, put together a list of eight different signs that a military is being politicized in this fashion. The Trump administration has exhibited six out of the eight.“The biggest theme is that we are seeing a number of checks on the executive fail at the same time — and that’s what’s making individual events seem more alarming than they might otherwise,” says Jessica Blankshain, a professor at the Naval War College (speaking not for the military but in a personal capacity).That Trump is trying to politicize the military does not mean he has succeeded. There are several signs, including Trump’s handpicked chair of the Joint Chiefs repudiating the president’s claims of a migrant invasion during congressional testimony, that the US military is resisting Trump’s politicization.But the events in Fort Bragg and Washington suggest that we are in the midst of a quiet crisis in civil-military relations in the United States — one whose implications for American democracy’s future could well be profound.The Trump crisis in civil-military relations, explainedA military is, by sheer fact of its existence, a threat to any civilian government. If you have an institution that controls the overwhelming bulk of weaponry in a society, it always has the physical capacity to seize control of the government at gunpoint. A key question for any government is how to convince the armed forces that they cannot or should not take power for themselves.Democracies typically do this through a process called “professionalization.” Soldiers are rigorously taught to think of themselves as a class of public servants, people trained to perform a specific job within defined parameters. Their ultimate loyalty is not to their generals or even individual presidents, but rather to the people and the constitutional order.Samuel Huntington, the late Harvard political scientist, is the canonical theorist of a professional military. In his book The Soldier and the State, he described optimal professionalization as a system of “objective control”: one in which the military retains autonomy in how they fight and plan for wars while deferring to politicians on whether and why to fight in the first place. In effect, they stay out of the politicians’ affairs while the politicians stay out of theirs.The idea of such a system is to emphasize to the military that they are professionals: Their responsibility isn’t deciding when to use force, but only to conduct operations as effectively as possible once ordered to engage in them. There is thus a strict firewall between military affairs, on the one hand, and policy-political affairs on the other.Typically, the chief worry is that the military breaches this bargain: that, for example, a general starts speaking out against elected officials’ policies in ways that undermine civilian control. This is not a hypothetical fear in the United States, with the most famous such example being Gen. Douglas MacArthur’s insubordination during the Korean War. Thankfully, not even MacArthur attempted the worst-case version of military overstep — a coup.But in backsliding democracies like the modern United States, where the chief executive is attempting an anti-democratic power grab, the military poses a very different kind of threat to democracy — in fact, something akin to the exact opposite of the typical scenario.In such cases, the issue isn’t the military inserting itself into politics but rather the civilians dragging them into it in ways that upset the democratic political order. The worst-case scenario is that the military acts on presidential directives to use force against domestic dissenters, destroying democracy not by ignoring civilian orders, but by following them.There are two ways to arrive at such a worst-case scenario, both of which are in evidence in the early days of Trump 2.0.First is politicization: an intentional attack on the constraints against partisan activity inside the professional ranks.Many of Pete Hegseth’s major moves as secretary of defense fit this bill, including his decisions to fire nonwhite and female generals seen as politically unreliable and his effort to undermine the independence of the military’s lawyers. The breaches in protocol at Fort Bragg are both consequences and causes of politicization: They could only happen in an environment of loosened constraint, and they might encourage more overt political action if gone unpunished.The second pathway to breakdown is the weaponization of professionalism against itself. Here, Trump exploits the military’s deference to politicians by ordering it to engage in undemocratic (and even questionably legal) activities. In practice, this looks a lot like the LA deployments, and, more specifically, the lack of any visible military pushback. While the military readily agreeing to deployments is normally a good sign — that civilian control is holding — these aren’t normal times. And this isn’t a normal deployment, but rather one that comes uncomfortably close to the military being ordered to assist in repressing overwhelmingly peaceful demonstrations against executive abuses of power.“It’s really been pretty uncommon to use the military for law enforcement,” says David Burbach, another Naval War College professor (also speaking personally). “This is really bringing the military into frontline law enforcement when. … these are really not huge disturbances.”This, then, is the crisis: an incremental and slow-rolling effort by the Trump administration to erode the norms and procedures designed to prevent the military from being used as a tool of domestic repression. Is it time to panic?Among the experts I spoke with, there was consensus that the military’s professional and nonpartisan ethos was weakening. This isn’t just because of Trump, but his terms — the first to a degree, and now the second acutely — are major stressors.Yet there was no consensus on just how much military nonpartisanship has eroded — that is, how close we are to a moment when the US military might be willing to follow obviously authoritarian orders.For all its faults, the US military’s professional ethos is a really important part of its identity and self-conception. While few soldiers may actually read Sam Huntington or similar scholars, the general idea that they serve the people and the republic is a bedrock principle among the ranks. There is a reason why the United States has never, in over 250 years of governance, experienced a military coup — or even come particularly close to one.In theory, this ethos should also galvanize resistance to Trump’s efforts at politicization. Soldiers are not unthinking automatons: While they are trained to follow commands, they are explicitly obligated to refuse illegal orders, even coming from the president. The more aggressive Trump’s efforts to use the military as a tool of repression gets, the more likely there is to be resistance.Or, at least theoretically.The truth is that we don’t really know how the US military will respond to a situation like this. Like so many of Trump’s second-term policies, their efforts to bend the military to their will are unprecedented — actions with no real parallel in the modern history of the American military. Experts can only make informed guesses, based on their sense of US military culture as well as comparisons to historical and foreign cases.For this reason, there are probably only two things we can say with confidence.First, what we’ve seen so far is not yet sufficient evidence to declare that the military is in Trump’s thrall. The signs of decay are too limited to ground any conclusions that the longstanding professional norm is entirely gone.“We have seen a few things that are potentially alarming about erosion of the military’s non-partisan norm. But not in a way that’s definitive at this point,” Blankshain says.Second, the stressors on this tradition are going to keep piling on. Trump’s record makes it exceptionally clear that he wants the military to serve him personally — and that he, and Hegseth, will keep working to make it so. This means we really are in the midst of a quiet crisis, and will likely remain so for the foreseeable future.“The fact that he’s getting the troops to cheer for booing Democratic leaders at a time when there’s actually [a deployment to] a blue city and a blue state…he is ordering the troops to take a side,” Saideman says. “There may not be a coherent plan behind this. But there are a lot of things going on that are all in the same direction.”See More: Politics