• The Samsung XR headset is coming soon. People in the tech world seem to care a lot about it, but honestly, it’s just another gadget. There are tons of features being talked about, and some excitement, I guess. But is it really that special? Probably not. Just another accessory for those who feel like spending their money on tech stuff. Anyway, if you're into this kind of thing, you might want to read more about it. Or not.

    #SamsungXR #TechNews #Gadgets #VirtualReality #Boredom
    The Samsung XR headset is coming soon. People in the tech world seem to care a lot about it, but honestly, it’s just another gadget. There are tons of features being talked about, and some excitement, I guess. But is it really that special? Probably not. Just another accessory for those who feel like spending their money on tech stuff. Anyway, if you're into this kind of thing, you might want to read more about it. Or not. #SamsungXR #TechNews #Gadgets #VirtualReality #Boredom
    Tout ce qu’il faut retenir sur le casque XR de Samsung à venir
    Très attendu par les amateurs de tech, le casque XR de Samsung fait déjà beaucoup […] Cet article Tout ce qu’il faut retenir sur le casque XR de Samsung à venir a été publié sur REALITE-VIRTUELLE.COM.
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  • Bruno Collet and his team talked about their short film "Atomik Tour" at the National Animation Film Festival. The film is a 12-minute stop-motion piece about dark tourism, set in some kind of forbidden zone. It’s supposed to be fantastic, but honestly, it just sounds a bit… dull. Anyway, if you’re into this kind of stuff, you might find it interesting. Just another film event, I guess.

    #DarkTourism #StopMotion #AtomikTour #BrunoCollet #AnimationFilm
    Bruno Collet and his team talked about their short film "Atomik Tour" at the National Animation Film Festival. The film is a 12-minute stop-motion piece about dark tourism, set in some kind of forbidden zone. It’s supposed to be fantastic, but honestly, it just sounds a bit… dull. Anyway, if you’re into this kind of stuff, you might find it interesting. Just another film event, I guess. #DarkTourism #StopMotion #AtomikTour #BrunoCollet #AnimationFilm
    Dark Tourism et Stop-Motion : les coulisses d’Atomik Tour de Bruno Collet
    A l’occasion du Festival National du Film d’Animation, le réalisateur Bruno Collet (connu entre autres pour son court-métrage Mémorable) et une partie de son équipe ont proposé un retour sur Atomik Tour. Ce court métrage est un film fanta
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  • Four science-based rules that will make your conversations flow

    One of the four pillars of good conversation is levity. You needn’t be a comedian, you can but have some funTetra Images, LLC/Alamy
    Conversation lies at the heart of our relationships – yet many of us find it surprisingly hard to talk to others. We may feel anxious at the thought of making small talk with strangers and struggle to connect with the people who are closest to us. If that sounds familiar, Alison Wood Brooks hopes to help. She is a professor at Harvard Business School, where she teaches an oversubscribed course called “TALK: How to talk gooder in business and life”, and the author of a new book, Talk: The science of conversation and the art of being ourselves. Both offer four key principles for more meaningful exchanges. Conversations are inherently unpredictable, says Wood Brooks, but they follow certain rules – and knowing their architecture makes us more comfortable with what is outside of our control. New Scientist asked her about the best ways to apply this research to our own chats.
    David Robson: Talking about talking feels quite meta. Do you ever find yourself critiquing your own performance?
    Alison Wood Brooks: There are so many levels of “meta-ness”. I have often felt like I’m floating over the room, watching conversations unfold, even as I’m involved in them myself. I teach a course at Harvard, andall get to experience this feeling as well. There can be an uncomfortable period of hypervigilance, but I hope that dissipates over time as they develop better habits. There is a famous quote from Charlie Parker, who was a jazz saxophonist. He said something like, “Practise, practise, practise, and then when you get on stage, let it all go and just wail.” I think that’s my approach to conversation. Even when you’re hyper-aware of conversation dynamics, you have to remember the true delight of being with another human mind, and never lose the magic of being together. Think ahead, but once you’re talking, let it all go and just wail.

    Reading your book, I learned that a good way to enliven a conversation is to ask someone why they are passionate about what they do. So, where does your passion for conversation come from?
    I have two answers to this question. One is professional. Early in my professorship at Harvard, I had been studying emotions by exploring how people talk about their feelings and the balance between what we feel inside and how we express that to others. And I realised I just had this deep, profound interest in figuring out how people talk to each other about everything, not just their feelings. We now have scientific tools that allow us to capture conversations and analyse them at large scale. Natural language processing, machine learning, the advent of AI – all this allows us to take huge swathes of transcript data and process it much more efficiently.

    Receive a weekly dose of discovery in your inbox.

    Sign up to newsletter

    The personal answer is that I’m an identical twin, and I spent my whole life, from the moment I opened my newborn eyes, existing next to a person who’s an exact copy of myself. It was like observing myself at very close range, interacting with the world, interacting with other people. I could see when she said and did things well, and I could try to do that myself. And I saw when her jokes failed, or she stumbled over her words – I tried to avoid those mistakes. It was a very fortunate form of feedback that not a lot of people get. And then, as a twin, you’ve got this person sharing a bedroom, sharing all your clothes, going to all the same parties and playing on the same sports teams, so we were just constantly in conversation with each other. You reached this level of shared reality that is so incredible, and I’ve spent the rest of my life trying to help other people get there in their relationships, too.
    “TALK” cleverly captures your framework for better conversations: topics, asking, levity and kindness. Let’s start at the beginning. How should we decide what to talk about?
    My first piece of advice is to prepare. Some people do this naturally. They already think about the things that they should talk about with somebody before they see them. They should lean into this habit. Some of my students, however, think it’s crazy. They think preparation will make the conversation seem rigid and forced and overly scripted. But just because you’ve thought ahead about what you might talk about doesn’t mean you have to talk about those things once the conversation is underway. It does mean, however, that you always have an idea waiting for you when you’re not sure what to talk about next. Having just one topic in your back pocket can help you in those anxiety-ridden moments. It makes things more fluent, which is important for establishing a connection. Choosing a topic is not only important at the start of a conversation. We’re constantly making decisions about whether we should stay on one subject, drift to something else or totally shift gears and go somewhere wildly different.
    Sometimes the topic of conversation is obvious. Even then, knowing when to switch to a new one can be trickyMartin Parr/Magnum Photos
    What’s your advice when making these decisions?
    There are three very clear signs that suggest that it’s time to switch topics. The first is longer mutual pauses. The second is more uncomfortable laughter, which we use to fill the space that we would usually fill excitedly with good content. And the third sign is redundancy. Once you start repeating things that have already been said on the topic, it’s a sign that you should move to something else.
    After an average conversation, most people feel like they’ve covered the right number of topics. But if you ask people after conversations that didn’t go well, they’ll more often say that they didn’t talk about enough things, rather than that they talked about too many things. This suggests that a common mistake is lingering too long on a topic after you’ve squeezed all the juice out of it.
    The second element of TALK is asking questions. I think a lot of us have heard the advice to ask more questions, yet many people don’t apply it. Why do you think that is?
    Many years of research have shown that the human mind is remarkably egocentric. Often, we are so focused on our own perspective that we forget to even ask someone else to share what’s in their mind. Another reason is fear. You’re interested in the other person, and you know you should ask them questions, but you’re afraid of being too intrusive, or that you will reveal your own incompetence, because you feel you should know the answer already.

    What kinds of questions should we be asking – and avoiding?
    In the book, I talk about the power of follow-up questions that build on anything that your partner has just said. It shows that you heard them, that you care and that you want to know more. Even one follow-up question can springboard us away from shallow talk into something deeper and more meaningful.
    There are, however, some bad patterns of question asking, such as “boomerasking”. Michael Yeomansand I have a recent paper about this, and oh my gosh, it’s been such fun to study. It’s a play on the word boomerang: it comes back to the person who threw it. If I ask you what you had for breakfast, and you tell me you had Special K and banana, and then I say, “Well, let me tell you about my breakfast, because, boy, was it delicious” – that’s boomerasking. Sometimes it’s a thinly veiled way of bragging or complaining, but sometimes I think people are genuinely interested to hear from their partner, but then the partner’s answer reminds them so much of their own life that they can’t help but start sharing their perspective. In our research, we have found that this makes your partner feel like you weren’t interested in their perspective, so it seems very insincere. Sharing your own perspective is important. It’s okay at some point to bring the conversation back to yourself. But don’t do it so soon that it makes your partner feel like you didn’t hear their answer or care about it.
    Research by Alison Wood Brooks includes a recent study on “boomerasking”, a pitfall you should avoid to make conversations flowJanelle Bruno
    What are the benefits of levity?
    When we think of conversations that haven’t gone well, we often think of moments of hostility, anger or disagreement, but a quiet killer of conversation is boredom. Levity is the antidote. These small moments of sparkle or fizz can pull us back in and make us feel engaged with each other again.
    Our research has shown that we give status and respect to people who make us feel good, so much so that in a group of people, a person who can land even one appropriate joke is more likely to be voted as the leader. And the joke doesn’t even need to be very funny! It’s the fact that they were confident enough to try it and competent enough to read the room.
    Do you have any practical steps that people can apply to generate levity, even if they’re not a natural comedian?
    Levity is not just about being funny. In fact, aiming to be a comedian is not the right goal. When we watch stand-up on Netflix, comedians have rehearsed those jokes and honed them and practised them for a long time, and they’re delivering them in a monologue to an audience. It’s a completely different task from a live conversation. In real dialogue, what everybody is looking for is to feel engaged, and that doesn’t require particularly funny jokes or elaborate stories. When you see opportunities to make it fun or lighten the mood, that’s what you need to grab. It can come through a change to a new, fresh topic, or calling back to things that you talked about earlier in the conversation or earlier in your relationship. These callbacks – which sometimes do refer to something funny – are such a nice way of showing that you’ve listened and remembered. A levity move could also involve giving sincere compliments to other people. When you think nice things, when you admire someone, make sure you say it out loud.

    This brings us to the last element of TALK: kindness. Why do we so often fail to be as kind as we would like?
    Wobbles in kindness often come back to our egocentrism. Research shows that we underestimate how much other people’s perspectives differ from our own, and we forget that we have the tools to ask other people directly in conversation for their perspective. Being a kinder conversationalist is about trying to focus on your partner’s perspective and then figuring what they need and helping them to get it.
    Finally, what is your number one tip for readers to have a better conversation the next time they speak to someone?
    Every conversation is surprisingly tricky and complex. When things don’t go perfectly, give yourself and others more grace. There will be trips and stumbles and then a little grace can go very, very far.
    Topics:
    #four #sciencebased #rules #that #will
    Four science-based rules that will make your conversations flow
    One of the four pillars of good conversation is levity. You needn’t be a comedian, you can but have some funTetra Images, LLC/Alamy Conversation lies at the heart of our relationships – yet many of us find it surprisingly hard to talk to others. We may feel anxious at the thought of making small talk with strangers and struggle to connect with the people who are closest to us. If that sounds familiar, Alison Wood Brooks hopes to help. She is a professor at Harvard Business School, where she teaches an oversubscribed course called “TALK: How to talk gooder in business and life”, and the author of a new book, Talk: The science of conversation and the art of being ourselves. Both offer four key principles for more meaningful exchanges. Conversations are inherently unpredictable, says Wood Brooks, but they follow certain rules – and knowing their architecture makes us more comfortable with what is outside of our control. New Scientist asked her about the best ways to apply this research to our own chats. David Robson: Talking about talking feels quite meta. Do you ever find yourself critiquing your own performance? Alison Wood Brooks: There are so many levels of “meta-ness”. I have often felt like I’m floating over the room, watching conversations unfold, even as I’m involved in them myself. I teach a course at Harvard, andall get to experience this feeling as well. There can be an uncomfortable period of hypervigilance, but I hope that dissipates over time as they develop better habits. There is a famous quote from Charlie Parker, who was a jazz saxophonist. He said something like, “Practise, practise, practise, and then when you get on stage, let it all go and just wail.” I think that’s my approach to conversation. Even when you’re hyper-aware of conversation dynamics, you have to remember the true delight of being with another human mind, and never lose the magic of being together. Think ahead, but once you’re talking, let it all go and just wail. Reading your book, I learned that a good way to enliven a conversation is to ask someone why they are passionate about what they do. So, where does your passion for conversation come from? I have two answers to this question. One is professional. Early in my professorship at Harvard, I had been studying emotions by exploring how people talk about their feelings and the balance between what we feel inside and how we express that to others. And I realised I just had this deep, profound interest in figuring out how people talk to each other about everything, not just their feelings. We now have scientific tools that allow us to capture conversations and analyse them at large scale. Natural language processing, machine learning, the advent of AI – all this allows us to take huge swathes of transcript data and process it much more efficiently. Receive a weekly dose of discovery in your inbox. Sign up to newsletter The personal answer is that I’m an identical twin, and I spent my whole life, from the moment I opened my newborn eyes, existing next to a person who’s an exact copy of myself. It was like observing myself at very close range, interacting with the world, interacting with other people. I could see when she said and did things well, and I could try to do that myself. And I saw when her jokes failed, or she stumbled over her words – I tried to avoid those mistakes. It was a very fortunate form of feedback that not a lot of people get. And then, as a twin, you’ve got this person sharing a bedroom, sharing all your clothes, going to all the same parties and playing on the same sports teams, so we were just constantly in conversation with each other. You reached this level of shared reality that is so incredible, and I’ve spent the rest of my life trying to help other people get there in their relationships, too. “TALK” cleverly captures your framework for better conversations: topics, asking, levity and kindness. Let’s start at the beginning. How should we decide what to talk about? My first piece of advice is to prepare. Some people do this naturally. They already think about the things that they should talk about with somebody before they see them. They should lean into this habit. Some of my students, however, think it’s crazy. They think preparation will make the conversation seem rigid and forced and overly scripted. But just because you’ve thought ahead about what you might talk about doesn’t mean you have to talk about those things once the conversation is underway. It does mean, however, that you always have an idea waiting for you when you’re not sure what to talk about next. Having just one topic in your back pocket can help you in those anxiety-ridden moments. It makes things more fluent, which is important for establishing a connection. Choosing a topic is not only important at the start of a conversation. We’re constantly making decisions about whether we should stay on one subject, drift to something else or totally shift gears and go somewhere wildly different. Sometimes the topic of conversation is obvious. Even then, knowing when to switch to a new one can be trickyMartin Parr/Magnum Photos What’s your advice when making these decisions? There are three very clear signs that suggest that it’s time to switch topics. The first is longer mutual pauses. The second is more uncomfortable laughter, which we use to fill the space that we would usually fill excitedly with good content. And the third sign is redundancy. Once you start repeating things that have already been said on the topic, it’s a sign that you should move to something else. After an average conversation, most people feel like they’ve covered the right number of topics. But if you ask people after conversations that didn’t go well, they’ll more often say that they didn’t talk about enough things, rather than that they talked about too many things. This suggests that a common mistake is lingering too long on a topic after you’ve squeezed all the juice out of it. The second element of TALK is asking questions. I think a lot of us have heard the advice to ask more questions, yet many people don’t apply it. Why do you think that is? Many years of research have shown that the human mind is remarkably egocentric. Often, we are so focused on our own perspective that we forget to even ask someone else to share what’s in their mind. Another reason is fear. You’re interested in the other person, and you know you should ask them questions, but you’re afraid of being too intrusive, or that you will reveal your own incompetence, because you feel you should know the answer already. What kinds of questions should we be asking – and avoiding? In the book, I talk about the power of follow-up questions that build on anything that your partner has just said. It shows that you heard them, that you care and that you want to know more. Even one follow-up question can springboard us away from shallow talk into something deeper and more meaningful. There are, however, some bad patterns of question asking, such as “boomerasking”. Michael Yeomansand I have a recent paper about this, and oh my gosh, it’s been such fun to study. It’s a play on the word boomerang: it comes back to the person who threw it. If I ask you what you had for breakfast, and you tell me you had Special K and banana, and then I say, “Well, let me tell you about my breakfast, because, boy, was it delicious” – that’s boomerasking. Sometimes it’s a thinly veiled way of bragging or complaining, but sometimes I think people are genuinely interested to hear from their partner, but then the partner’s answer reminds them so much of their own life that they can’t help but start sharing their perspective. In our research, we have found that this makes your partner feel like you weren’t interested in their perspective, so it seems very insincere. Sharing your own perspective is important. It’s okay at some point to bring the conversation back to yourself. But don’t do it so soon that it makes your partner feel like you didn’t hear their answer or care about it. Research by Alison Wood Brooks includes a recent study on “boomerasking”, a pitfall you should avoid to make conversations flowJanelle Bruno What are the benefits of levity? When we think of conversations that haven’t gone well, we often think of moments of hostility, anger or disagreement, but a quiet killer of conversation is boredom. Levity is the antidote. These small moments of sparkle or fizz can pull us back in and make us feel engaged with each other again. Our research has shown that we give status and respect to people who make us feel good, so much so that in a group of people, a person who can land even one appropriate joke is more likely to be voted as the leader. And the joke doesn’t even need to be very funny! It’s the fact that they were confident enough to try it and competent enough to read the room. Do you have any practical steps that people can apply to generate levity, even if they’re not a natural comedian? Levity is not just about being funny. In fact, aiming to be a comedian is not the right goal. When we watch stand-up on Netflix, comedians have rehearsed those jokes and honed them and practised them for a long time, and they’re delivering them in a monologue to an audience. It’s a completely different task from a live conversation. In real dialogue, what everybody is looking for is to feel engaged, and that doesn’t require particularly funny jokes or elaborate stories. When you see opportunities to make it fun or lighten the mood, that’s what you need to grab. It can come through a change to a new, fresh topic, or calling back to things that you talked about earlier in the conversation or earlier in your relationship. These callbacks – which sometimes do refer to something funny – are such a nice way of showing that you’ve listened and remembered. A levity move could also involve giving sincere compliments to other people. When you think nice things, when you admire someone, make sure you say it out loud. This brings us to the last element of TALK: kindness. Why do we so often fail to be as kind as we would like? Wobbles in kindness often come back to our egocentrism. Research shows that we underestimate how much other people’s perspectives differ from our own, and we forget that we have the tools to ask other people directly in conversation for their perspective. Being a kinder conversationalist is about trying to focus on your partner’s perspective and then figuring what they need and helping them to get it. Finally, what is your number one tip for readers to have a better conversation the next time they speak to someone? Every conversation is surprisingly tricky and complex. When things don’t go perfectly, give yourself and others more grace. There will be trips and stumbles and then a little grace can go very, very far. Topics: #four #sciencebased #rules #that #will
    WWW.NEWSCIENTIST.COM
    Four science-based rules that will make your conversations flow
    One of the four pillars of good conversation is levity. You needn’t be a comedian, you can but have some funTetra Images, LLC/Alamy Conversation lies at the heart of our relationships – yet many of us find it surprisingly hard to talk to others. We may feel anxious at the thought of making small talk with strangers and struggle to connect with the people who are closest to us. If that sounds familiar, Alison Wood Brooks hopes to help. She is a professor at Harvard Business School, where she teaches an oversubscribed course called “TALK: How to talk gooder in business and life”, and the author of a new book, Talk: The science of conversation and the art of being ourselves. Both offer four key principles for more meaningful exchanges. Conversations are inherently unpredictable, says Wood Brooks, but they follow certain rules – and knowing their architecture makes us more comfortable with what is outside of our control. New Scientist asked her about the best ways to apply this research to our own chats. David Robson: Talking about talking feels quite meta. Do you ever find yourself critiquing your own performance? Alison Wood Brooks: There are so many levels of “meta-ness”. I have often felt like I’m floating over the room, watching conversations unfold, even as I’m involved in them myself. I teach a course at Harvard, and [my students] all get to experience this feeling as well. There can be an uncomfortable period of hypervigilance, but I hope that dissipates over time as they develop better habits. There is a famous quote from Charlie Parker, who was a jazz saxophonist. He said something like, “Practise, practise, practise, and then when you get on stage, let it all go and just wail.” I think that’s my approach to conversation. Even when you’re hyper-aware of conversation dynamics, you have to remember the true delight of being with another human mind, and never lose the magic of being together. Think ahead, but once you’re talking, let it all go and just wail. Reading your book, I learned that a good way to enliven a conversation is to ask someone why they are passionate about what they do. So, where does your passion for conversation come from? I have two answers to this question. One is professional. Early in my professorship at Harvard, I had been studying emotions by exploring how people talk about their feelings and the balance between what we feel inside and how we express that to others. And I realised I just had this deep, profound interest in figuring out how people talk to each other about everything, not just their feelings. We now have scientific tools that allow us to capture conversations and analyse them at large scale. Natural language processing, machine learning, the advent of AI – all this allows us to take huge swathes of transcript data and process it much more efficiently. Receive a weekly dose of discovery in your inbox. Sign up to newsletter The personal answer is that I’m an identical twin, and I spent my whole life, from the moment I opened my newborn eyes, existing next to a person who’s an exact copy of myself. It was like observing myself at very close range, interacting with the world, interacting with other people. I could see when she said and did things well, and I could try to do that myself. And I saw when her jokes failed, or she stumbled over her words – I tried to avoid those mistakes. It was a very fortunate form of feedback that not a lot of people get. And then, as a twin, you’ve got this person sharing a bedroom, sharing all your clothes, going to all the same parties and playing on the same sports teams, so we were just constantly in conversation with each other. You reached this level of shared reality that is so incredible, and I’ve spent the rest of my life trying to help other people get there in their relationships, too. “TALK” cleverly captures your framework for better conversations: topics, asking, levity and kindness. Let’s start at the beginning. How should we decide what to talk about? My first piece of advice is to prepare. Some people do this naturally. They already think about the things that they should talk about with somebody before they see them. They should lean into this habit. Some of my students, however, think it’s crazy. They think preparation will make the conversation seem rigid and forced and overly scripted. But just because you’ve thought ahead about what you might talk about doesn’t mean you have to talk about those things once the conversation is underway. It does mean, however, that you always have an idea waiting for you when you’re not sure what to talk about next. Having just one topic in your back pocket can help you in those anxiety-ridden moments. It makes things more fluent, which is important for establishing a connection. Choosing a topic is not only important at the start of a conversation. We’re constantly making decisions about whether we should stay on one subject, drift to something else or totally shift gears and go somewhere wildly different. Sometimes the topic of conversation is obvious. Even then, knowing when to switch to a new one can be trickyMartin Parr/Magnum Photos What’s your advice when making these decisions? There are three very clear signs that suggest that it’s time to switch topics. The first is longer mutual pauses. The second is more uncomfortable laughter, which we use to fill the space that we would usually fill excitedly with good content. And the third sign is redundancy. Once you start repeating things that have already been said on the topic, it’s a sign that you should move to something else. After an average conversation, most people feel like they’ve covered the right number of topics. But if you ask people after conversations that didn’t go well, they’ll more often say that they didn’t talk about enough things, rather than that they talked about too many things. This suggests that a common mistake is lingering too long on a topic after you’ve squeezed all the juice out of it. The second element of TALK is asking questions. I think a lot of us have heard the advice to ask more questions, yet many people don’t apply it. Why do you think that is? Many years of research have shown that the human mind is remarkably egocentric. Often, we are so focused on our own perspective that we forget to even ask someone else to share what’s in their mind. Another reason is fear. You’re interested in the other person, and you know you should ask them questions, but you’re afraid of being too intrusive, or that you will reveal your own incompetence, because you feel you should know the answer already. What kinds of questions should we be asking – and avoiding? In the book, I talk about the power of follow-up questions that build on anything that your partner has just said. It shows that you heard them, that you care and that you want to know more. Even one follow-up question can springboard us away from shallow talk into something deeper and more meaningful. There are, however, some bad patterns of question asking, such as “boomerasking”. Michael Yeomans [at Imperial College London] and I have a recent paper about this, and oh my gosh, it’s been such fun to study. It’s a play on the word boomerang: it comes back to the person who threw it. If I ask you what you had for breakfast, and you tell me you had Special K and banana, and then I say, “Well, let me tell you about my breakfast, because, boy, was it delicious” – that’s boomerasking. Sometimes it’s a thinly veiled way of bragging or complaining, but sometimes I think people are genuinely interested to hear from their partner, but then the partner’s answer reminds them so much of their own life that they can’t help but start sharing their perspective. In our research, we have found that this makes your partner feel like you weren’t interested in their perspective, so it seems very insincere. Sharing your own perspective is important. It’s okay at some point to bring the conversation back to yourself. But don’t do it so soon that it makes your partner feel like you didn’t hear their answer or care about it. Research by Alison Wood Brooks includes a recent study on “boomerasking”, a pitfall you should avoid to make conversations flowJanelle Bruno What are the benefits of levity? When we think of conversations that haven’t gone well, we often think of moments of hostility, anger or disagreement, but a quiet killer of conversation is boredom. Levity is the antidote. These small moments of sparkle or fizz can pull us back in and make us feel engaged with each other again. Our research has shown that we give status and respect to people who make us feel good, so much so that in a group of people, a person who can land even one appropriate joke is more likely to be voted as the leader. And the joke doesn’t even need to be very funny! It’s the fact that they were confident enough to try it and competent enough to read the room. Do you have any practical steps that people can apply to generate levity, even if they’re not a natural comedian? Levity is not just about being funny. In fact, aiming to be a comedian is not the right goal. When we watch stand-up on Netflix, comedians have rehearsed those jokes and honed them and practised them for a long time, and they’re delivering them in a monologue to an audience. It’s a completely different task from a live conversation. In real dialogue, what everybody is looking for is to feel engaged, and that doesn’t require particularly funny jokes or elaborate stories. When you see opportunities to make it fun or lighten the mood, that’s what you need to grab. It can come through a change to a new, fresh topic, or calling back to things that you talked about earlier in the conversation or earlier in your relationship. These callbacks – which sometimes do refer to something funny – are such a nice way of showing that you’ve listened and remembered. A levity move could also involve giving sincere compliments to other people. When you think nice things, when you admire someone, make sure you say it out loud. This brings us to the last element of TALK: kindness. Why do we so often fail to be as kind as we would like? Wobbles in kindness often come back to our egocentrism. Research shows that we underestimate how much other people’s perspectives differ from our own, and we forget that we have the tools to ask other people directly in conversation for their perspective. Being a kinder conversationalist is about trying to focus on your partner’s perspective and then figuring what they need and helping them to get it. Finally, what is your number one tip for readers to have a better conversation the next time they speak to someone? Every conversation is surprisingly tricky and complex. When things don’t go perfectly, give yourself and others more grace. There will be trips and stumbles and then a little grace can go very, very far. Topics:
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  • Apple WWDC 2025: News and analysis

    Apple’s Worldwide Developers Conference 2025 saw a range of announcements that offered a glimpse into the future of Apple’s software design and artificial intelligencestrategy, highlighted by a new design language called  Liquid Glass and by Apple Intelligence news.

    Liquid Glass is designed to add translucency and dynamic movement to Apple’s user interface across iPhones, iPads, Macs, Apple Watches, and Apple TVs. The overhaul aims to make interactions with elements like buttons and sidebars adapt contextually.

    However, the real news of WWDC could be what we didn’t see.  Analysts had high expectations for Apple’s AI strategy, and while Apple Intelligence was talked about, many market watchers reported that it lacked the innovation that have come from Google’s and Microsoft’s generative AIrollouts.

    The question of whether Apple is playing catch-up lingered at WWDC 2025, and comments from Apple execs about delays to a significant AI overhaul for Siri were apparently interpreted as a setback by investors, leading to a negative reaction and drop in stock price.

    Follow this page for Computerworld‘s coverage of WWDC25.

    WWDC25 news and analysis

    Apple’s AI Revolution: Insights from WWDC

    June 13, 2025: At Apple’s big developer event, developers were served a feast of AI-related updates, including APIs that let them use Apple Intelligence in their apps and ChatGPT-augmentation from within Xcode. As a development environment, Apple has secured its future, with Macs forming the most computationally performant systems you can affordably purchase for the job.

    For developers, Apple’s tools get a lot better for AI

    June 12, 2025: Apple announced one important AI update at WWDC this week, the introduction of support for third-party large language models such as ChatGPT from within Xcode. It’s a big step that should benefit developers, accelerating app development.

    WWDC 25: What’s new for Apple and the enterprise?

    June 11, 2025: Beyond its new Liquid Glass UI and other major improvements across its operating systems, Apple introduced a hoard of changes, tweaks, and enhancements for IT admins at WWDC 2025.

    What we know so far about Apple’s Liquid Glass UI

    June 10, 2025: What Apple has tried to achieve with Liquid Glass is to bring together the optical quality of glass and the fluidity of liquid to emphasize transparency and lighting when using your devices. 

    WWDC first look: How Apple is improving its ecosystem

    June 9, 2025: While the new user interface design Apple execs highlighted at this year’s Worldwide Developers Conferencemight have been a bit of an eye-candy distraction, Apple’s enterprise users were not forgotten.

    Apple infuses AI into the Vision Pro

    June 8, 2025: Sluggish sales of Apple’s Vision Pro mixed reality headset haven’t dampened the company’s enthusiasm for advancing the device’s 3D computing experience, which now incorporates AI to deliver richer context and experiences.

    WWDC: Apple is about to unlock international business

    June 4, 2025: One of the more exciting pre-WWDC rumors is that Apple is preparing to make language problems go away by implementing focused artificial intelligence in Messages, which will apparently be able to translate incoming and outgoing messages on the fly. 
    #apple #wwdc #news #analysis
    Apple WWDC 2025: News and analysis
    Apple’s Worldwide Developers Conference 2025 saw a range of announcements that offered a glimpse into the future of Apple’s software design and artificial intelligencestrategy, highlighted by a new design language called  Liquid Glass and by Apple Intelligence news. Liquid Glass is designed to add translucency and dynamic movement to Apple’s user interface across iPhones, iPads, Macs, Apple Watches, and Apple TVs. The overhaul aims to make interactions with elements like buttons and sidebars adapt contextually. However, the real news of WWDC could be what we didn’t see.  Analysts had high expectations for Apple’s AI strategy, and while Apple Intelligence was talked about, many market watchers reported that it lacked the innovation that have come from Google’s and Microsoft’s generative AIrollouts. The question of whether Apple is playing catch-up lingered at WWDC 2025, and comments from Apple execs about delays to a significant AI overhaul for Siri were apparently interpreted as a setback by investors, leading to a negative reaction and drop in stock price. Follow this page for Computerworld‘s coverage of WWDC25. WWDC25 news and analysis Apple’s AI Revolution: Insights from WWDC June 13, 2025: At Apple’s big developer event, developers were served a feast of AI-related updates, including APIs that let them use Apple Intelligence in their apps and ChatGPT-augmentation from within Xcode. As a development environment, Apple has secured its future, with Macs forming the most computationally performant systems you can affordably purchase for the job. For developers, Apple’s tools get a lot better for AI June 12, 2025: Apple announced one important AI update at WWDC this week, the introduction of support for third-party large language models such as ChatGPT from within Xcode. It’s a big step that should benefit developers, accelerating app development. WWDC 25: What’s new for Apple and the enterprise? June 11, 2025: Beyond its new Liquid Glass UI and other major improvements across its operating systems, Apple introduced a hoard of changes, tweaks, and enhancements for IT admins at WWDC 2025. What we know so far about Apple’s Liquid Glass UI June 10, 2025: What Apple has tried to achieve with Liquid Glass is to bring together the optical quality of glass and the fluidity of liquid to emphasize transparency and lighting when using your devices.  WWDC first look: How Apple is improving its ecosystem June 9, 2025: While the new user interface design Apple execs highlighted at this year’s Worldwide Developers Conferencemight have been a bit of an eye-candy distraction, Apple’s enterprise users were not forgotten. Apple infuses AI into the Vision Pro June 8, 2025: Sluggish sales of Apple’s Vision Pro mixed reality headset haven’t dampened the company’s enthusiasm for advancing the device’s 3D computing experience, which now incorporates AI to deliver richer context and experiences. WWDC: Apple is about to unlock international business June 4, 2025: One of the more exciting pre-WWDC rumors is that Apple is preparing to make language problems go away by implementing focused artificial intelligence in Messages, which will apparently be able to translate incoming and outgoing messages on the fly.  #apple #wwdc #news #analysis
    WWW.COMPUTERWORLD.COM
    Apple WWDC 2025: News and analysis
    Apple’s Worldwide Developers Conference 2025 saw a range of announcements that offered a glimpse into the future of Apple’s software design and artificial intelligence (AI) strategy, highlighted by a new design language called  Liquid Glass and by Apple Intelligence news. Liquid Glass is designed to add translucency and dynamic movement to Apple’s user interface across iPhones, iPads, Macs, Apple Watches, and Apple TVs. The overhaul aims to make interactions with elements like buttons and sidebars adapt contextually. However, the real news of WWDC could be what we didn’t see.  Analysts had high expectations for Apple’s AI strategy, and while Apple Intelligence was talked about, many market watchers reported that it lacked the innovation that have come from Google’s and Microsoft’s generative AI (genAI) rollouts. The question of whether Apple is playing catch-up lingered at WWDC 2025, and comments from Apple execs about delays to a significant AI overhaul for Siri were apparently interpreted as a setback by investors, leading to a negative reaction and drop in stock price. Follow this page for Computerworld‘s coverage of WWDC25. WWDC25 news and analysis Apple’s AI Revolution: Insights from WWDC June 13, 2025: At Apple’s big developer event, developers were served a feast of AI-related updates, including APIs that let them use Apple Intelligence in their apps and ChatGPT-augmentation from within Xcode. As a development environment, Apple has secured its future, with Macs forming the most computationally performant systems you can affordably purchase for the job. For developers, Apple’s tools get a lot better for AI June 12, 2025: Apple announced one important AI update at WWDC this week, the introduction of support for third-party large language models (LLM) such as ChatGPT from within Xcode. It’s a big step that should benefit developers, accelerating app development. WWDC 25: What’s new for Apple and the enterprise? June 11, 2025: Beyond its new Liquid Glass UI and other major improvements across its operating systems, Apple introduced a hoard of changes, tweaks, and enhancements for IT admins at WWDC 2025. What we know so far about Apple’s Liquid Glass UI June 10, 2025: What Apple has tried to achieve with Liquid Glass is to bring together the optical quality of glass and the fluidity of liquid to emphasize transparency and lighting when using your devices.  WWDC first look: How Apple is improving its ecosystem June 9, 2025: While the new user interface design Apple execs highlighted at this year’s Worldwide Developers Conference (WWDC) might have been a bit of an eye-candy distraction, Apple’s enterprise users were not forgotten. Apple infuses AI into the Vision Pro June 8, 2025: Sluggish sales of Apple’s Vision Pro mixed reality headset haven’t dampened the company’s enthusiasm for advancing the device’s 3D computing experience, which now incorporates AI to deliver richer context and experiences. WWDC: Apple is about to unlock international business June 4, 2025: One of the more exciting pre-WWDC rumors is that Apple is preparing to make language problems go away by implementing focused artificial intelligence in Messages, which will apparently be able to translate incoming and outgoing messages on the fly. 
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  • 6 Years to Make a Fan, G370A Budget Case, & Phanteks Technical Fan Discussion, ft. CTO

    Cases News 6 Years to Make a Fan, G370A Budget Case, & Phanteks Technical Fan Discussion, ft. CTOJune 9, 2025Last Updated: 2025-06-09We cover Phanteks’ new G370A budget case, the XT M3, and the Evolv X2 MatrixThe HighlightsPhanteks’ new X2 Matrix case has 900 LEDs and is aiming to be around Phanteks’ G370A is a case that includes 3x120mm fansThe company has a new T30-140 fan that required 6 years of engineering to makeTable of ContentsAutoTOC Grab a GN Tear-Down Toolkit to support our AD-FREE reviews and IN-DEPTH testing while also getting a high-quality, highly portable 10-piece toolkit that was custom designed for use with video cards for repasting and water block installation. Includes a portable roll bag, hook hangers for pegboards, a storage compartment, and instructional GPU disassembly cards.IntroWe visited Phanteks’ suite at Computex 2025 and the company showed off several cases along with a fan that took the company roughly 6 years to make.Editor's note: This was originally published on May 21, 2025 as a video. This content has been adapted to written format for this article and is unchanged from the original publication.CreditsHostSteve BurkeCamera, Video EditingMike GaglioneVitalii MakhnovetsWriting, Web EditingJimmy ThangPhanteks Matrix CasesWe’ve talked about Phanteks’ X2 case in the past but the company was showing off its new Matrix version, which has matrix LEDs. The X2 Matrix has 900 LEDs in a 10x90 layout. It’s supposed to be about to more expensive than the base X2, which means it should end up around   The interesting thing about the case is that the LEDs wrap around the chassis. In terms of communication, the LEDs connect to the motherboard via USB 2.0 and use SATA for power. This allows Phanteks to bypass a WinRing 0 type situation. Another Matrix case had 600 of them in a 10x60 LED configuration and is supposed to be about  Phanteks also has software that allows you to reconfigure what the LEDs display. When we got to the company’s suite, it had been programmed to say, “Gamers Nexus here,” which was cool to see. We also saw that the LEDs can also be used to highlight CPU temperature. Phanteks G370A Grab a GN15 Large Anti-Static Modmat to celebrate our 15th Anniversary and for a high-quality PC building work surface. The Modmat features useful PC building diagrams and is anti-static conductive. Purchases directly fund our work!Phanteks also showed off its G370A case, which is a case that includes 3x120mm fans in the front coupled with a mesh front that offers 38% hole porosity. The company tells us that manufacturing typically offers around 25% porosity.  It has a glass side panel and the back side panel of the case is just steel and has no ventilation. Taking a look at the placement of the front fans, we asked Phanteks why they weren’t higher on the case so the bottom fan could get more exposure to the bottom power supply shroud area and the answer the company gave us was simply clearance for a 360mm radiator at the top. There’s not a lot of room for the air coming into the shroud. Some of it will go through the cable pass-through if it’s empty. The back of the case features a drive mount.XTM3The company also showed off a Micro ATX case called the XTM3. It comes with 3 fans and is For its front panel, it has a unique punch out for its fans. The top panel is part standard ventilation but it does have one side that provides less airflow, which covers where the PSU would exhaust out of. The side panel does have punch-outs for the PSU, however. We don’t test power supplies, though that may change in the future. Power supplies can take a lot of thermal abuse, however, so we’re not super concerned here.  The case should be shipping in the next month or so and is 39.5 liters, which includes the feet. We appreciate that as not a lot of companies will factor that in. There’s also a lot of cable management depth on the back and the case also supports BTF. In addition, there’s a panel that clamps down all of the power supply cables. T30 FanPhanteks’ T30 fan took the company 6 years to make and is a 140mm fan. The company is competing with Noctua in the high-end fan space, but is going for a grey theme instead of brown. Phanteks CTO Tenzin Rongen Interview Visit our Patreon page to contribute a few dollars toward this website's operationAdditionally, when you purchase through links to retailers on our site, we may earn a small affiliate commission.Finally, we interviewed Phanteks CTO Tenzin Rongen to discuss technical details behind the company’s long-developed fans. Make sure to check it out in our video.
    #years #make #fan #g370a #budget
    6 Years to Make a Fan, G370A Budget Case, & Phanteks Technical Fan Discussion, ft. CTO
    Cases News 6 Years to Make a Fan, G370A Budget Case, & Phanteks Technical Fan Discussion, ft. CTOJune 9, 2025Last Updated: 2025-06-09We cover Phanteks’ new G370A budget case, the XT M3, and the Evolv X2 MatrixThe HighlightsPhanteks’ new X2 Matrix case has 900 LEDs and is aiming to be around Phanteks’ G370A is a case that includes 3x120mm fansThe company has a new T30-140 fan that required 6 years of engineering to makeTable of ContentsAutoTOC Grab a GN Tear-Down Toolkit to support our AD-FREE reviews and IN-DEPTH testing while also getting a high-quality, highly portable 10-piece toolkit that was custom designed for use with video cards for repasting and water block installation. Includes a portable roll bag, hook hangers for pegboards, a storage compartment, and instructional GPU disassembly cards.IntroWe visited Phanteks’ suite at Computex 2025 and the company showed off several cases along with a fan that took the company roughly 6 years to make.Editor's note: This was originally published on May 21, 2025 as a video. This content has been adapted to written format for this article and is unchanged from the original publication.CreditsHostSteve BurkeCamera, Video EditingMike GaglioneVitalii MakhnovetsWriting, Web EditingJimmy ThangPhanteks Matrix CasesWe’ve talked about Phanteks’ X2 case in the past but the company was showing off its new Matrix version, which has matrix LEDs. The X2 Matrix has 900 LEDs in a 10x90 layout. It’s supposed to be about to more expensive than the base X2, which means it should end up around   The interesting thing about the case is that the LEDs wrap around the chassis. In terms of communication, the LEDs connect to the motherboard via USB 2.0 and use SATA for power. This allows Phanteks to bypass a WinRing 0 type situation. Another Matrix case had 600 of them in a 10x60 LED configuration and is supposed to be about  Phanteks also has software that allows you to reconfigure what the LEDs display. When we got to the company’s suite, it had been programmed to say, “Gamers Nexus here,” which was cool to see. We also saw that the LEDs can also be used to highlight CPU temperature. Phanteks G370A Grab a GN15 Large Anti-Static Modmat to celebrate our 15th Anniversary and for a high-quality PC building work surface. The Modmat features useful PC building diagrams and is anti-static conductive. Purchases directly fund our work!Phanteks also showed off its G370A case, which is a case that includes 3x120mm fans in the front coupled with a mesh front that offers 38% hole porosity. The company tells us that manufacturing typically offers around 25% porosity.  It has a glass side panel and the back side panel of the case is just steel and has no ventilation. Taking a look at the placement of the front fans, we asked Phanteks why they weren’t higher on the case so the bottom fan could get more exposure to the bottom power supply shroud area and the answer the company gave us was simply clearance for a 360mm radiator at the top. There’s not a lot of room for the air coming into the shroud. Some of it will go through the cable pass-through if it’s empty. The back of the case features a drive mount.XTM3The company also showed off a Micro ATX case called the XTM3. It comes with 3 fans and is For its front panel, it has a unique punch out for its fans. The top panel is part standard ventilation but it does have one side that provides less airflow, which covers where the PSU would exhaust out of. The side panel does have punch-outs for the PSU, however. We don’t test power supplies, though that may change in the future. Power supplies can take a lot of thermal abuse, however, so we’re not super concerned here.  The case should be shipping in the next month or so and is 39.5 liters, which includes the feet. We appreciate that as not a lot of companies will factor that in. There’s also a lot of cable management depth on the back and the case also supports BTF. In addition, there’s a panel that clamps down all of the power supply cables. T30 FanPhanteks’ T30 fan took the company 6 years to make and is a 140mm fan. The company is competing with Noctua in the high-end fan space, but is going for a grey theme instead of brown. Phanteks CTO Tenzin Rongen Interview Visit our Patreon page to contribute a few dollars toward this website's operationAdditionally, when you purchase through links to retailers on our site, we may earn a small affiliate commission.Finally, we interviewed Phanteks CTO Tenzin Rongen to discuss technical details behind the company’s long-developed fans. Make sure to check it out in our video. #years #make #fan #g370a #budget
    GAMERSNEXUS.NET
    6 Years to Make a Fan, G370A Budget Case, & Phanteks Technical Fan Discussion, ft. CTO
    Cases News 6 Years to Make a Fan, G370A Budget Case, & Phanteks Technical Fan Discussion, ft. CTOJune 9, 2025Last Updated: 2025-06-09We cover Phanteks’ new G370A budget case, the XT M3, and the Evolv X2 MatrixThe HighlightsPhanteks’ new X2 Matrix case has 900 LEDs and is aiming to be around $200Phanteks’ G370A is a $60 case that includes 3x120mm fansThe company has a new T30-140 fan that required 6 years of engineering to makeTable of ContentsAutoTOC Grab a GN Tear-Down Toolkit to support our AD-FREE reviews and IN-DEPTH testing while also getting a high-quality, highly portable 10-piece toolkit that was custom designed for use with video cards for repasting and water block installation. Includes a portable roll bag, hook hangers for pegboards, a storage compartment, and instructional GPU disassembly cards.IntroWe visited Phanteks’ suite at Computex 2025 and the company showed off several cases along with a fan that took the company roughly 6 years to make.Editor's note: This was originally published on May 21, 2025 as a video. This content has been adapted to written format for this article and is unchanged from the original publication.CreditsHostSteve BurkeCamera, Video EditingMike GaglioneVitalii MakhnovetsWriting, Web EditingJimmy ThangPhanteks Matrix CasesWe’ve talked about Phanteks’ X2 case in the past but the company was showing off its new Matrix version, which has matrix LEDs. The X2 Matrix has 900 LEDs in a 10x90 layout. It’s supposed to be about $30 to $40 more expensive than the base X2, which means it should end up around $200.  The interesting thing about the case is that the LEDs wrap around the chassis. In terms of communication, the LEDs connect to the motherboard via USB 2.0 and use SATA for power. This allows Phanteks to bypass a WinRing 0 type situation. Another Matrix case had 600 of them in a 10x60 LED configuration and is supposed to be about $120. Phanteks also has software that allows you to reconfigure what the LEDs display. When we got to the company’s suite, it had been programmed to say, “Gamers Nexus here,” which was cool to see. We also saw that the LEDs can also be used to highlight CPU temperature. Phanteks G370A Grab a GN15 Large Anti-Static Modmat to celebrate our 15th Anniversary and for a high-quality PC building work surface. The Modmat features useful PC building diagrams and is anti-static conductive. Purchases directly fund our work! (or consider a direct donation or a Patreon contribution!)Phanteks also showed off its G370A case, which is a $60 case that includes 3x120mm fans in the front coupled with a mesh front that offers 38% hole porosity. The company tells us that manufacturing typically offers around 25% porosity.  It has a glass side panel and the back side panel of the case is just steel and has no ventilation. Taking a look at the placement of the front fans, we asked Phanteks why they weren’t higher on the case so the bottom fan could get more exposure to the bottom power supply shroud area and the answer the company gave us was simply clearance for a 360mm radiator at the top. There’s not a lot of room for the air coming into the shroud. Some of it will go through the cable pass-through if it’s empty. The back of the case features a drive mount.XTM3The company also showed off a Micro ATX case called the XTM3. It comes with 3 fans and is $70. For its front panel, it has a unique punch out for its fans. The top panel is part standard ventilation but it does have one side that provides less airflow, which covers where the PSU would exhaust out of. The side panel does have punch-outs for the PSU, however. We don’t test power supplies, though that may change in the future. Power supplies can take a lot of thermal abuse, however, so we’re not super concerned here.  The case should be shipping in the next month or so and is 39.5 liters, which includes the feet. We appreciate that as not a lot of companies will factor that in. There’s also a lot of cable management depth on the back and the case also supports BTF. In addition, there’s a panel that clamps down all of the power supply cables. T30 FanPhanteks’ T30 fan took the company 6 years to make and is a 140mm fan. The company is competing with Noctua in the high-end fan space, but is going for a grey theme instead of brown. Phanteks CTO Tenzin Rongen Interview Visit our Patreon page to contribute a few dollars toward this website's operation (or consider a direct donation or buying something from our GN Store!) Additionally, when you purchase through links to retailers on our site, we may earn a small affiliate commission.Finally, we interviewed Phanteks CTO Tenzin Rongen to discuss technical details behind the company’s long-developed fans. Make sure to check it out in our video.
    0 Comments 0 Shares 0 Reviews
  • CD Projekt RED: TW4 has console first development with a 60fps target; 60fps on Series S will be "extremely challenging"

    DriftingSpirit
    Member

    Oct 25, 2017

    18,563

    They note how they usually start with PC and scale down, but they will be doing it the other way around this time to avoid issues with the console versions.

    4:15 for console focus and 60fps
    38:50 for the Series S comment 

    bsigg
    Member

    Oct 25, 2017

    25,153Inside The Witcher 4 Unreal Engine 5 Tech Demo: CD Projekt RED + Epic Deep Dive Interview



    www.resetera.com

     

    Skot
    Member

    Oct 30, 2017

    645

    720p on Series S incoming
     

    Bulby
    Prophet of Truth
    Member

    Oct 29, 2017

    6,006

    Berlin

    I think think any series s user will be happy with a beautiful 900p 30fps
     

    Chronos
    Member

    Oct 27, 2017

    1,249

    This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation.
     

    HellofaMouse
    Member

    Oct 27, 2017

    8,551

    i wonder if this'll come out before the gen is over?

    good chance itll be a 2077 situation, cross-gen release with a broken ps6 version 

    logash
    Member

    Oct 27, 2017

    6,526

    This makes sense since they want to have good performance on lower end machines and they mentioned that it was easier to scale up than to scale down. They also mentioned their legacy on PC and how they plan on scaling it up high like they usually do on PC.
     

    KRT
    Member

    Aug 7, 2020

    247

    Series S was a mistake
     

    chris 1515
    Member

    Oct 27, 2017

    7,116

    Barcelona Spain

    The game have raytracing GI and reflection it will probably be 30 fps 600p-720p on Xbox Series S.
     

    bitcloudrzr
    Member

    May 31, 2018

    21,044

    Bulby said:

    I think think any series s user will be happy with a beautiful 900p 30fps

    Click to expand...
    Click to shrink...

     

    Yuuber
    Member

    Oct 28, 2017

    4,540

    KRT said:

    Series S was a mistake

    Click to expand...
    Click to shrink...

    Can we stop with these stupid takes? For all we know it sold as much as Series X, helped several games have better optimization on bigger consoles and it will definitely help optimizing newer games to the Nintendo Switch 2. 

    MANTRA
    Member

    Feb 21, 2024

    1,198

    No one who cares about 60fps should be buying a Series S, just make it 30fps.
     

    Roytheone
    Member

    Oct 25, 2017

    6,185

    Chronos said:

    This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation.

    Click to expand...
    Click to shrink...

    They can just go for 30 fps instead on the Series S. No need for a special deal for that, that's allowed. 

    Matterhorn
    Member

    Feb 6, 2019

    254

    United States

    Hoping for a very nice looking 30fps Switch 2 version.
     

    Universal Acclaim
    Member

    Oct 5, 2024

    2,617

    Maybe off topic, but is 30fps target not so important anymore for 2027 industry-leading graphics? GTA is mainly doing it for design/physics/etc. whch is why the game can't be scaled down to 720-900p/60fps?
     

    chris 1515
    Member

    Oct 27, 2017

    7,116

    Barcelona Spain

    Matterhorn said:

    Hoping for a very nice looking 30fps Switch 2 version.

    Click to expand...
    Click to shrink...

    It will be a full port a few years after like The Witcher 3., they don't use software lumen here. I doubt the Switch 2 Raytracing capaclity is high enough to use the same pipeline to produce the Switch 2 version.

    EDIT: And they probably need to redo all the assets.

    /

    Fortnite doesn't use Nanite and Lumen on Switch 2. 

    Last edited: Yesterday at 4:18 PM

    bitcloudrzr
    Member

    May 31, 2018

    21,044

    Universal Acclaim said:

    Maybe off topic, but is 30fps target not so important anymore for 2027 industry-leading graphics? GTA is mainly doing it for design/physics/etc. whch is why the graphics can't be scaled down to 720p/60fps?

    Click to expand...
    Click to shrink...

    Graphics are the part of the game that can be scaled, it is CPU load that is the more difficult part, although devs have actually made cuts in the latter to increase performance mode fps viability. Even with this focus on 60fps performance modes, they are always going to have room to make a higher fidelity 30fps mode. Specifically with UE5 though, performance has been such a disaster all around and Epic seems to be taking it seriously now.
     

    Greywaren
    Member

    Jul 16, 2019

    13,530

    Spain

    60 fps target is fantastic, I wish it was the norm.
     

    julia crawford
    Took the red AND the blue pills
    Member

    Oct 27, 2017

    40,709

    i am very ok with lower fps on the series s, it is far more palatable than severe resolution drops with upscaling artifacts.
     

    Spoit
    Member

    Oct 28, 2017

    5,599

    Chronos said:

    This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation.

    Click to expand...
    Click to shrink...

    And yet people keep talking about somehow getting PS6 games to work on the sony portable, which is probably going to be like half as powerful as a PS5, like that won't hold games back
     

    PLASTICA-MAN
    Member

    Oct 26, 2017

    29,563

    chris 1515 said:

    The game have raytracing GI and reflection it will probably be 30 fps 600p-720p on Xbox Series S.

    Click to expand...
    Click to shrink...

    There is kinda a misconception of how Lumen and the hybrid RT is handled in UE5 titles. AO is also part of the ray traced pipeline through the HW Lumen too.
    Just shadows are handled separately from the RT system by using VSM which in final look behvae quite like RT shadows in shape, same how FF16 handled the shadows looking like RT ones while it isn't traced.
    UE5 can still trace shadows if they want to push things even further. 

    overthewaves
    Member

    Sep 30, 2020

    1,203

    What about the PS5 handheld?
     

    nullpotential
    Member

    Jun 24, 2024

    87

    KRT said:

    Series S was a mistake

    Click to expand...
    Click to shrink...

    Consoles were a mistake. 

    GPU
    Member

    Oct 10, 2024

    1,075

    I really dont think Series S/X will be much of a factor by the time this game comes out.
     

    Lashley
    <<Tag Here>>
    Member

    Oct 25, 2017

    65,679

    Just make series s 480p 30fps
     

    pappacone
    Member

    Jan 10, 2020

    4,076

    Greywaren said:

    60 fps target is fantastic, I wish it was the norm.

    Click to expand...
    Click to shrink...

    It pretty much is
     

    Super
    Studied the Buster Sword
    Member

    Jan 29, 2022

    13,601

    I hope they can pull 60 FPS off in the full game.
     

    Theorry
    Member

    Oct 27, 2017

    69,045

    "target"

    Uh huh. We know how that is gonna go. 

    Jakartalado
    Member

    Oct 27, 2017

    2,818

    São Paulo, Brazil

    Skot said:

    720p on Series S incoming

    Click to expand...
    Click to shrink...

    If the PS5 is internally at 720p up to 900p, I seriously doubt that. 

    Revoltoftheunique
    Member

    Jan 23, 2022

    2,312

    It will be unstable 60fps with lots of stuttering.
     

    defaltoption
    Plug in a controller and enter the Konami code
    The Fallen

    Oct 27, 2017

    12,485

    Austin

    KRT said:

    Series S was a mistake

    Click to expand...
    Click to shrink...

    With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid.
     

    Horns
    Member

    Dec 7, 2018

    3,423

    I hope Microsoft drops the requirement for Series S by the time this comes out.
     

    chris 1515
    Member

    Oct 27, 2017

    7,116

    Barcelona Spain

    PLASTICA-MAN said:

    There is kinda a misconception of how Lumen and the hybrid RT is handled in UE5 titles. AO is also part of the ray traced pipeline through the HW Lumen too.

    Just shadows are handled separately from the RT system by using VSM which in final look behvae quite like RT shadows in shape, same how FF16 handled the shadows looking like RT ones while it isn't traced.
    UE5 can still trace shadows if they want to push things even further.
    Click to expand...
    Click to shrink...

    Yes indirect shadows are handled by hardware lumen. But at the end ot doesn¡t change my comment. i think the game will be 600´720p at 30 fps on Series S. 

    bitcloudrzr
    Member

    May 31, 2018

    21,044

    Spoit said:

    And yet people keep talking about somehow getting PS6 games to work on the sony portable, which is probably going to be like half as powerful as a PS5, like that won't hold games back

    Click to expand...
    Click to shrink...

    Has it been confirmed that Sony is going to have release requirements like the XS?
     

    Commander Shepherd
    Member

    Jan 27, 2023

    173

    Anyone remember when no load screens was talked about for Witcher 3?
     

    chris 1515
    Member

    Oct 27, 2017

    7,116

    Barcelona Spain

    No this is probably different than most game are doing it here the main focus is the 60 fps mode and after they can create a balancedand 30 fps mode.

    This is not the other way around. 

    stanman
    Member

    Feb 13, 2025

    235

    defaltoption said:

    With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid.

    Click to expand...
    Click to shrink...

    And your mistake is comparing a PC graphics card to a console. 

    PLASTICA-MAN
    Member

    Oct 26, 2017

    29,563

    chris 1515 said:

    Yes indirect shadows are handled by hardware lumen. But at the end ot doesn¡t change my comment. i think the game will be 600´720p at 30 fps on Series S.

    Click to expand...
    Click to shrink...

    Yes. I am sure Series S will have HW solution but probably at 30 FPS. that would be a miracle if they achieve 60 FPS. 

    ArchedThunder
    Uncle Beerus
    Member

    Oct 25, 2017

    21,278

    chris 1515 said:

    It will be a full port a few years after like The Witcher 3., they don't use software lumen here. I doubt the Switch 2 Raytracing capaclity is high enough to use the same pipeline to produce the Switch 2 version.

    EDIT: And they probably need to redo all the assets.

    /

    Fortnite doesn't use Nanite and Lumen on Switch 2.
    Click to expand...
    Click to shrink...

    Fortnite not using Lumen or Nanite at launch doesn't mean they can't run well on Switch 2. It's a launch port and they prioritized clean IQ and 60fps. I wouldn't be surprised to see them added later. Also it's not like the ray tracing in a Witcher 3 port has to match PS5, there's a lot of scaling back that can be done with ray tracing without ripping out the kitchen sink. Software lumen is also likely to be an option on P.
     

    jroc74
    Member

    Oct 27, 2017

    34,465

    Interesting times ahead....

    bitcloudrzr said:

    Has it been confirmed that Sony is going to have release requirements like the XS?

    Click to expand...
    Click to shrink...

    Your know good n well everything about this rumor has been confirmed.

    /S 

    Derbel McDillet
    ▲ Legend ▲
    Member

    Nov 23, 2022

    25,250

    Chronos said:

    This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation.

    Click to expand...
    Click to shrink...

    How does this sound like a Cyberpunk issue? They didn't say they can't get it to work on the S.
     

    defaltoption
    Plug in a controller and enter the Konami code
    The Fallen

    Oct 27, 2017

    12,485

    Austin

    stanman said:

    And your mistake is comparing a PC graphics card to a console.

    Click to expand...
    Click to shrink...

     

    reksveks
    Member

    May 17, 2022

    7,628

    Horns said:

    I hope Microsoft drops the requirement for Series S by the time this comes out.

    Click to expand...
    Click to shrink...

    why? dev can make it 30 fps on series s and 60 fps on series x if needed.

    if they aren't or don't have to drop it for gta vi, they probably ain't dropping it for tw4. 

    chris 1515
    Member

    Oct 27, 2017

    7,116

    Barcelona Spain

    defaltoption said:

    With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid.

    Click to expand...
    Click to shrink...

    No the consoles won't hold back your 5090 because the game is created with hardware lumen, RT reflection, virtual shadows maps and Nanite plus Nanite vegetation in minds. Maybe Nanite character too in final version?

    If the game was made with software lumen as the base it would have holding back your 5090...

    Your PC will have much better IQ, framerate and better raytracing with Megalightand better raytracing settings in general. 

    bitcloudrzr
    Member

    May 31, 2018

    21,044

    jroc74 said:

    Interesting times ahead....

    Your know good n well everything about this rumor has been confirmed.

    /S
    Click to expand...
    Click to shrink...

    Sony is like the opposite of a platform holder "forcing" adoption, for better or worse.
     

    defaltoption
    Plug in a controller and enter the Konami code
    The Fallen

    Oct 27, 2017

    12,485

    Austin

    chris 1515 said:

    No the consoles won't hold back yout 5090 because the game is created with hardware lumen, RT reflection, virtual shadows maps and Nanite plus Nanite vegetation in minds. Maybe Nanite character too in final version?

    If the game was made with software lumen as the base it would have holding back your 5090...

    Your PC will have much better IQ, framerate and better raytracing with Megalightand better raytracing settings in general.
    Click to expand...
    Click to shrink...

    Exactly, the series s is not a "mistake" or holding any version of the game on console or even PC back, that's what I'm saying to the person I replied to, its stupid to say that.
     

    cursed beef
    Member

    Jan 3, 2021

    998

    Have to imagine MS will lift the Series S parity clause when the next consoles launch. Which will be before/around the time W4 hits, right?
     

    Alvis
    Saw the truth behind the copied door
    Member

    Oct 25, 2017

    12,270

    EU

    Chronos said:

    This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation.

    Click to expand...
    Click to shrink...

    ? they said that 60 FPS on Series S is challenging, not the act of releasing the game there at all. The game can simply run at 30 FPS on Series S if they can't pull off 60 FPS. Or have a 40 FPS mode in lieu of 60 FPS.

    The CPU and storage speed differences between last gen and current gen were gigantic. This isn't even remotely close to a comparable situation. 

    defaltoption
    Plug in a controller and enter the Konami code
    The Fallen

    Oct 27, 2017

    12,485

    Austin

    misqoute post
     

    jroc74
    Member

    Oct 27, 2017

    34,465

    defaltoption said:

    With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid.

    Click to expand...
    Click to shrink...

    Ah yes, clearly 5090 cards are the vast majority of the minimum requirements for PC games.

    How can anyone say this with a straight face anymore when there are now PC games running on a Steam Deck.

    At least ppl saying that about the Series S are comparing it to other consoles.

    That said, it is interesting they are focusing on consoles first, then PC. 
    #projekt #red #tw4 #has #console
    CD Projekt RED: TW4 has console first development with a 60fps target; 60fps on Series S will be "extremely challenging"
    DriftingSpirit Member Oct 25, 2017 18,563 They note how they usually start with PC and scale down, but they will be doing it the other way around this time to avoid issues with the console versions. 4:15 for console focus and 60fps 38:50 for the Series S comment  bsigg Member Oct 25, 2017 25,153Inside The Witcher 4 Unreal Engine 5 Tech Demo: CD Projekt RED + Epic Deep Dive Interview www.resetera.com   Skot Member Oct 30, 2017 645 720p on Series S incoming   Bulby Prophet of Truth Member Oct 29, 2017 6,006 Berlin I think think any series s user will be happy with a beautiful 900p 30fps   Chronos Member Oct 27, 2017 1,249 This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation.   HellofaMouse Member Oct 27, 2017 8,551 i wonder if this'll come out before the gen is over? good chance itll be a 2077 situation, cross-gen release with a broken ps6 version  logash Member Oct 27, 2017 6,526 This makes sense since they want to have good performance on lower end machines and they mentioned that it was easier to scale up than to scale down. They also mentioned their legacy on PC and how they plan on scaling it up high like they usually do on PC.   KRT Member Aug 7, 2020 247 Series S was a mistake   chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain The game have raytracing GI and reflection it will probably be 30 fps 600p-720p on Xbox Series S.   bitcloudrzr Member May 31, 2018 21,044 Bulby said: I think think any series s user will be happy with a beautiful 900p 30fps Click to expand... Click to shrink...   Yuuber Member Oct 28, 2017 4,540 KRT said: Series S was a mistake Click to expand... Click to shrink... Can we stop with these stupid takes? For all we know it sold as much as Series X, helped several games have better optimization on bigger consoles and it will definitely help optimizing newer games to the Nintendo Switch 2.  MANTRA Member Feb 21, 2024 1,198 No one who cares about 60fps should be buying a Series S, just make it 30fps.   Roytheone Member Oct 25, 2017 6,185 Chronos said: This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation. Click to expand... Click to shrink... They can just go for 30 fps instead on the Series S. No need for a special deal for that, that's allowed.  Matterhorn Member Feb 6, 2019 254 United States Hoping for a very nice looking 30fps Switch 2 version.   Universal Acclaim Member Oct 5, 2024 2,617 Maybe off topic, but is 30fps target not so important anymore for 2027 industry-leading graphics? GTA is mainly doing it for design/physics/etc. whch is why the game can't be scaled down to 720-900p/60fps?   chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain Matterhorn said: Hoping for a very nice looking 30fps Switch 2 version. Click to expand... Click to shrink... It will be a full port a few years after like The Witcher 3., they don't use software lumen here. I doubt the Switch 2 Raytracing capaclity is high enough to use the same pipeline to produce the Switch 2 version. EDIT: And they probably need to redo all the assets. / Fortnite doesn't use Nanite and Lumen on Switch 2.  Last edited: Yesterday at 4:18 PM bitcloudrzr Member May 31, 2018 21,044 Universal Acclaim said: Maybe off topic, but is 30fps target not so important anymore for 2027 industry-leading graphics? GTA is mainly doing it for design/physics/etc. whch is why the graphics can't be scaled down to 720p/60fps? Click to expand... Click to shrink... Graphics are the part of the game that can be scaled, it is CPU load that is the more difficult part, although devs have actually made cuts in the latter to increase performance mode fps viability. Even with this focus on 60fps performance modes, they are always going to have room to make a higher fidelity 30fps mode. Specifically with UE5 though, performance has been such a disaster all around and Epic seems to be taking it seriously now.   Greywaren Member Jul 16, 2019 13,530 Spain 60 fps target is fantastic, I wish it was the norm.   julia crawford Took the red AND the blue pills Member Oct 27, 2017 40,709 i am very ok with lower fps on the series s, it is far more palatable than severe resolution drops with upscaling artifacts.   Spoit Member Oct 28, 2017 5,599 Chronos said: This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation. Click to expand... Click to shrink... And yet people keep talking about somehow getting PS6 games to work on the sony portable, which is probably going to be like half as powerful as a PS5, like that won't hold games back   PLASTICA-MAN Member Oct 26, 2017 29,563 chris 1515 said: The game have raytracing GI and reflection it will probably be 30 fps 600p-720p on Xbox Series S. Click to expand... Click to shrink... There is kinda a misconception of how Lumen and the hybrid RT is handled in UE5 titles. AO is also part of the ray traced pipeline through the HW Lumen too. Just shadows are handled separately from the RT system by using VSM which in final look behvae quite like RT shadows in shape, same how FF16 handled the shadows looking like RT ones while it isn't traced. UE5 can still trace shadows if they want to push things even further.  overthewaves Member Sep 30, 2020 1,203 What about the PS5 handheld?   nullpotential Member Jun 24, 2024 87 KRT said: Series S was a mistake Click to expand... Click to shrink... Consoles were a mistake.  GPU Member Oct 10, 2024 1,075 I really dont think Series S/X will be much of a factor by the time this game comes out.   Lashley <<Tag Here>> Member Oct 25, 2017 65,679 Just make series s 480p 30fps   pappacone Member Jan 10, 2020 4,076 Greywaren said: 60 fps target is fantastic, I wish it was the norm. Click to expand... Click to shrink... It pretty much is   Super Studied the Buster Sword Member Jan 29, 2022 13,601 I hope they can pull 60 FPS off in the full game.   Theorry Member Oct 27, 2017 69,045 "target" Uh huh. We know how that is gonna go.  Jakartalado Member Oct 27, 2017 2,818 São Paulo, Brazil Skot said: 720p on Series S incoming Click to expand... Click to shrink... If the PS5 is internally at 720p up to 900p, I seriously doubt that.  Revoltoftheunique Member Jan 23, 2022 2,312 It will be unstable 60fps with lots of stuttering.   defaltoption Plug in a controller and enter the Konami code The Fallen Oct 27, 2017 12,485 Austin KRT said: Series S was a mistake Click to expand... Click to shrink... With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid.   Horns Member Dec 7, 2018 3,423 I hope Microsoft drops the requirement for Series S by the time this comes out.   chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain PLASTICA-MAN said: There is kinda a misconception of how Lumen and the hybrid RT is handled in UE5 titles. AO is also part of the ray traced pipeline through the HW Lumen too. Just shadows are handled separately from the RT system by using VSM which in final look behvae quite like RT shadows in shape, same how FF16 handled the shadows looking like RT ones while it isn't traced. UE5 can still trace shadows if they want to push things even further. Click to expand... Click to shrink... Yes indirect shadows are handled by hardware lumen. But at the end ot doesn¡t change my comment. i think the game will be 600´720p at 30 fps on Series S.  bitcloudrzr Member May 31, 2018 21,044 Spoit said: And yet people keep talking about somehow getting PS6 games to work on the sony portable, which is probably going to be like half as powerful as a PS5, like that won't hold games back Click to expand... Click to shrink... Has it been confirmed that Sony is going to have release requirements like the XS?   Commander Shepherd Member Jan 27, 2023 173 Anyone remember when no load screens was talked about for Witcher 3?   chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain No this is probably different than most game are doing it here the main focus is the 60 fps mode and after they can create a balancedand 30 fps mode. This is not the other way around.  stanman Member Feb 13, 2025 235 defaltoption said: With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid. Click to expand... Click to shrink... And your mistake is comparing a PC graphics card to a console.  PLASTICA-MAN Member Oct 26, 2017 29,563 chris 1515 said: Yes indirect shadows are handled by hardware lumen. But at the end ot doesn¡t change my comment. i think the game will be 600´720p at 30 fps on Series S. Click to expand... Click to shrink... Yes. I am sure Series S will have HW solution but probably at 30 FPS. that would be a miracle if they achieve 60 FPS.  ArchedThunder Uncle Beerus Member Oct 25, 2017 21,278 chris 1515 said: It will be a full port a few years after like The Witcher 3., they don't use software lumen here. I doubt the Switch 2 Raytracing capaclity is high enough to use the same pipeline to produce the Switch 2 version. EDIT: And they probably need to redo all the assets. / Fortnite doesn't use Nanite and Lumen on Switch 2. Click to expand... Click to shrink... Fortnite not using Lumen or Nanite at launch doesn't mean they can't run well on Switch 2. It's a launch port and they prioritized clean IQ and 60fps. I wouldn't be surprised to see them added later. Also it's not like the ray tracing in a Witcher 3 port has to match PS5, there's a lot of scaling back that can be done with ray tracing without ripping out the kitchen sink. Software lumen is also likely to be an option on P.   jroc74 Member Oct 27, 2017 34,465 Interesting times ahead.... bitcloudrzr said: Has it been confirmed that Sony is going to have release requirements like the XS? Click to expand... Click to shrink... Your know good n well everything about this rumor has been confirmed. /S  Derbel McDillet ▲ Legend ▲ Member Nov 23, 2022 25,250 Chronos said: This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation. Click to expand... Click to shrink... How does this sound like a Cyberpunk issue? They didn't say they can't get it to work on the S.   defaltoption Plug in a controller and enter the Konami code The Fallen Oct 27, 2017 12,485 Austin stanman said: And your mistake is comparing a PC graphics card to a console. Click to expand... Click to shrink...   reksveks Member May 17, 2022 7,628 Horns said: I hope Microsoft drops the requirement for Series S by the time this comes out. Click to expand... Click to shrink... why? dev can make it 30 fps on series s and 60 fps on series x if needed. if they aren't or don't have to drop it for gta vi, they probably ain't dropping it for tw4.  chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain defaltoption said: With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid. Click to expand... Click to shrink... No the consoles won't hold back your 5090 because the game is created with hardware lumen, RT reflection, virtual shadows maps and Nanite plus Nanite vegetation in minds. Maybe Nanite character too in final version? If the game was made with software lumen as the base it would have holding back your 5090... Your PC will have much better IQ, framerate and better raytracing with Megalightand better raytracing settings in general.  bitcloudrzr Member May 31, 2018 21,044 jroc74 said: Interesting times ahead.... Your know good n well everything about this rumor has been confirmed. /S Click to expand... Click to shrink... Sony is like the opposite of a platform holder "forcing" adoption, for better or worse.   defaltoption Plug in a controller and enter the Konami code The Fallen Oct 27, 2017 12,485 Austin chris 1515 said: No the consoles won't hold back yout 5090 because the game is created with hardware lumen, RT reflection, virtual shadows maps and Nanite plus Nanite vegetation in minds. Maybe Nanite character too in final version? If the game was made with software lumen as the base it would have holding back your 5090... Your PC will have much better IQ, framerate and better raytracing with Megalightand better raytracing settings in general. Click to expand... Click to shrink... Exactly, the series s is not a "mistake" or holding any version of the game on console or even PC back, that's what I'm saying to the person I replied to, its stupid to say that.   cursed beef Member Jan 3, 2021 998 Have to imagine MS will lift the Series S parity clause when the next consoles launch. Which will be before/around the time W4 hits, right?   Alvis Saw the truth behind the copied door Member Oct 25, 2017 12,270 EU Chronos said: This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation. Click to expand... Click to shrink... ? they said that 60 FPS on Series S is challenging, not the act of releasing the game there at all. The game can simply run at 30 FPS on Series S if they can't pull off 60 FPS. Or have a 40 FPS mode in lieu of 60 FPS. The CPU and storage speed differences between last gen and current gen were gigantic. This isn't even remotely close to a comparable situation.  defaltoption Plug in a controller and enter the Konami code The Fallen Oct 27, 2017 12,485 Austin misqoute post   jroc74 Member Oct 27, 2017 34,465 defaltoption said: With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid. Click to expand... Click to shrink... Ah yes, clearly 5090 cards are the vast majority of the minimum requirements for PC games. How can anyone say this with a straight face anymore when there are now PC games running on a Steam Deck. At least ppl saying that about the Series S are comparing it to other consoles. That said, it is interesting they are focusing on consoles first, then PC.  #projekt #red #tw4 #has #console
    WWW.RESETERA.COM
    CD Projekt RED: TW4 has console first development with a 60fps target; 60fps on Series S will be "extremely challenging"
    DriftingSpirit Member Oct 25, 2017 18,563 They note how they usually start with PC and scale down, but they will be doing it the other way around this time to avoid issues with the console versions. 4:15 for console focus and 60fps 38:50 for the Series S comment  bsigg Member Oct 25, 2017 25,153 [DF] Inside The Witcher 4 Unreal Engine 5 Tech Demo: CD Projekt RED + Epic Deep Dive Interview https://www.youtube.com/watch?v=OplYN2MMI4Q www.resetera.com   Skot Member Oct 30, 2017 645 720p on Series S incoming   Bulby Prophet of Truth Member Oct 29, 2017 6,006 Berlin I think think any series s user will be happy with a beautiful 900p 30fps   Chronos Member Oct 27, 2017 1,249 This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation.   HellofaMouse Member Oct 27, 2017 8,551 i wonder if this'll come out before the gen is over? good chance itll be a 2077 situation, cross-gen release with a broken ps6 version  logash Member Oct 27, 2017 6,526 This makes sense since they want to have good performance on lower end machines and they mentioned that it was easier to scale up than to scale down. They also mentioned their legacy on PC and how they plan on scaling it up high like they usually do on PC.   KRT Member Aug 7, 2020 247 Series S was a mistake   chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain The game have raytracing GI and reflection it will probably be 30 fps 600p-720p on Xbox Series S.   bitcloudrzr Member May 31, 2018 21,044 Bulby said: I think think any series s user will be happy with a beautiful 900p 30fps Click to expand... Click to shrink...   Yuuber Member Oct 28, 2017 4,540 KRT said: Series S was a mistake Click to expand... Click to shrink... Can we stop with these stupid takes? For all we know it sold as much as Series X, helped several games have better optimization on bigger consoles and it will definitely help optimizing newer games to the Nintendo Switch 2.  MANTRA Member Feb 21, 2024 1,198 No one who cares about 60fps should be buying a Series S, just make it 30fps.   Roytheone Member Oct 25, 2017 6,185 Chronos said: This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation. Click to expand... Click to shrink... They can just go for 30 fps instead on the Series S. No need for a special deal for that, that's allowed.  Matterhorn Member Feb 6, 2019 254 United States Hoping for a very nice looking 30fps Switch 2 version.   Universal Acclaim Member Oct 5, 2024 2,617 Maybe off topic, but is 30fps target not so important anymore for 2027 industry-leading graphics? GTA is mainly doing it for design/physics/etc. whch is why the game can't be scaled down to 720-900p/60fps?   chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain Matterhorn said: Hoping for a very nice looking 30fps Switch 2 version. Click to expand... Click to shrink... It will be a full port a few years after like The Witcher 3., they don't use software lumen here. I doubt the Switch 2 Raytracing capaclity is high enough to use the same pipeline to produce the Switch 2 version. EDIT: And they probably need to redo all the assets. https://www.reddit.com/r/FortNiteBR/comments/1l4a1o4/fortnite_on_the_switch_2_looks_great_these_low/ Fortnite doesn't use Nanite and Lumen on Switch 2.  Last edited: Yesterday at 4:18 PM bitcloudrzr Member May 31, 2018 21,044 Universal Acclaim said: Maybe off topic, but is 30fps target not so important anymore for 2027 industry-leading graphics? GTA is mainly doing it for design/physics/etc. whch is why the graphics can't be scaled down to 720p/60fps? Click to expand... Click to shrink... Graphics are the part of the game that can be scaled, it is CPU load that is the more difficult part, although devs have actually made cuts in the latter to increase performance mode fps viability. Even with this focus on 60fps performance modes, they are always going to have room to make a higher fidelity 30fps mode. Specifically with UE5 though, performance has been such a disaster all around and Epic seems to be taking it seriously now.   Greywaren Member Jul 16, 2019 13,530 Spain 60 fps target is fantastic, I wish it was the norm.   julia crawford Took the red AND the blue pills Member Oct 27, 2017 40,709 i am very ok with lower fps on the series s, it is far more palatable than severe resolution drops with upscaling artifacts.   Spoit Member Oct 28, 2017 5,599 Chronos said: This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation. Click to expand... Click to shrink... And yet people keep talking about somehow getting PS6 games to work on the sony portable, which is probably going to be like half as powerful as a PS5, like that won't hold games back   PLASTICA-MAN Member Oct 26, 2017 29,563 chris 1515 said: The game have raytracing GI and reflection it will probably be 30 fps 600p-720p on Xbox Series S. Click to expand... Click to shrink... There is kinda a misconception of how Lumen and the hybrid RT is handled in UE5 titles. AO is also part of the ray traced pipeline through the HW Lumen too. Just shadows are handled separately from the RT system by using VSM which in final look behvae quite like RT shadows in shape, same how FF16 handled the shadows looking like RT ones while it isn't traced. UE5 can still trace shadows if they want to push things even further.  overthewaves Member Sep 30, 2020 1,203 What about the PS5 handheld?   nullpotential Member Jun 24, 2024 87 KRT said: Series S was a mistake Click to expand... Click to shrink... Consoles were a mistake.  GPU Member Oct 10, 2024 1,075 I really dont think Series S/X will be much of a factor by the time this game comes out.   Lashley <<Tag Here>> Member Oct 25, 2017 65,679 Just make series s 480p 30fps   pappacone Member Jan 10, 2020 4,076 Greywaren said: 60 fps target is fantastic, I wish it was the norm. Click to expand... Click to shrink... It pretty much is   Super Studied the Buster Sword Member Jan 29, 2022 13,601 I hope they can pull 60 FPS off in the full game.   Theorry Member Oct 27, 2017 69,045 "target" Uh huh. We know how that is gonna go.  Jakartalado Member Oct 27, 2017 2,818 São Paulo, Brazil Skot said: 720p on Series S incoming Click to expand... Click to shrink... If the PS5 is internally at 720p up to 900p, I seriously doubt that.  Revoltoftheunique Member Jan 23, 2022 2,312 It will be unstable 60fps with lots of stuttering.   defaltoption Plug in a controller and enter the Konami code The Fallen Oct 27, 2017 12,485 Austin KRT said: Series S was a mistake Click to expand... Click to shrink... With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid.   Horns Member Dec 7, 2018 3,423 I hope Microsoft drops the requirement for Series S by the time this comes out.   chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain PLASTICA-MAN said: There is kinda a misconception of how Lumen and the hybrid RT is handled in UE5 titles. AO is also part of the ray traced pipeline through the HW Lumen too. Just shadows are handled separately from the RT system by using VSM which in final look behvae quite like RT shadows in shape, same how FF16 handled the shadows looking like RT ones while it isn't traced. UE5 can still trace shadows if they want to push things even further. Click to expand... Click to shrink... Yes indirect shadows are handled by hardware lumen. But at the end ot doesn¡t change my comment. i think the game will be 600´720p at 30 fps on Series S.  bitcloudrzr Member May 31, 2018 21,044 Spoit said: And yet people keep talking about somehow getting PS6 games to work on the sony portable, which is probably going to be like half as powerful as a PS5, like that won't hold games back Click to expand... Click to shrink... Has it been confirmed that Sony is going to have release requirements like the XS?   Commander Shepherd Member Jan 27, 2023 173 Anyone remember when no load screens was talked about for Witcher 3?   chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain No this is probably different than most game are doing it here the main focus is the 60 fps mode and after they can create a balanced(40 fps) and 30 fps mode. This is not the other way around.  stanman Member Feb 13, 2025 235 defaltoption said: With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid. Click to expand... Click to shrink... And your mistake is comparing a PC graphics card to a console.  PLASTICA-MAN Member Oct 26, 2017 29,563 chris 1515 said: Yes indirect shadows are handled by hardware lumen. But at the end ot doesn¡t change my comment. i think the game will be 600´720p at 30 fps on Series S. Click to expand... Click to shrink... Yes. I am sure Series S will have HW solution but probably at 30 FPS. that would be a miracle if they achieve 60 FPS.  ArchedThunder Uncle Beerus Member Oct 25, 2017 21,278 chris 1515 said: It will be a full port a few years after like The Witcher 3., they don't use software lumen here. I doubt the Switch 2 Raytracing capaclity is high enough to use the same pipeline to produce the Switch 2 version. EDIT: And they probably need to redo all the assets. https://www.reddit.com/r/FortNiteBR/comments/1l4a1o4/fortnite_on_the_switch_2_looks_great_these_low/ Fortnite doesn't use Nanite and Lumen on Switch 2. Click to expand... Click to shrink... Fortnite not using Lumen or Nanite at launch doesn't mean they can't run well on Switch 2. It's a launch port and they prioritized clean IQ and 60fps. I wouldn't be surprised to see them added later. Also it's not like the ray tracing in a Witcher 3 port has to match PS5, there's a lot of scaling back that can be done with ray tracing without ripping out the kitchen sink. Software lumen is also likely to be an option on P.   jroc74 Member Oct 27, 2017 34,465 Interesting times ahead.... bitcloudrzr said: Has it been confirmed that Sony is going to have release requirements like the XS? Click to expand... Click to shrink... Your know good n well everything about this rumor has been confirmed. /S  Derbel McDillet ▲ Legend ▲ Member Nov 23, 2022 25,250 Chronos said: This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation. Click to expand... Click to shrink... How does this sound like a Cyberpunk issue? They didn't say they can't get it to work on the S.   defaltoption Plug in a controller and enter the Konami code The Fallen Oct 27, 2017 12,485 Austin stanman said: And your mistake is comparing a PC graphics card to a console. Click to expand... Click to shrink...   reksveks Member May 17, 2022 7,628 Horns said: I hope Microsoft drops the requirement for Series S by the time this comes out. Click to expand... Click to shrink... why? dev can make it 30 fps on series s and 60 fps on series x if needed. if they aren't or don't have to drop it for gta vi, they probably ain't dropping it for tw4.  chris 1515 Member Oct 27, 2017 7,116 Barcelona Spain defaltoption said: With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid. Click to expand... Click to shrink... No the consoles won't hold back your 5090 because the game is created with hardware lumen, RT reflection, virtual shadows maps and Nanite plus Nanite vegetation in minds. Maybe Nanite character too in final version? If the game was made with software lumen as the base it would have holding back your 5090... Your PC will have much better IQ, framerate and better raytracing with Megalight(direct raytraced shadows with tons of lighe source) and better raytracing settings in general.  bitcloudrzr Member May 31, 2018 21,044 jroc74 said: Interesting times ahead.... Your know good n well everything about this rumor has been confirmed. /S Click to expand... Click to shrink... Sony is like the opposite of a platform holder "forcing" adoption, for better or worse.   defaltoption Plug in a controller and enter the Konami code The Fallen Oct 27, 2017 12,485 Austin chris 1515 said: No the consoles won't hold back yout 5090 because the game is created with hardware lumen, RT reflection, virtual shadows maps and Nanite plus Nanite vegetation in minds. Maybe Nanite character too in final version? If the game was made with software lumen as the base it would have holding back your 5090... Your PC will have much better IQ, framerate and better raytracing with Megalight(direct raytraced shadows) and better raytracing settings in general. Click to expand... Click to shrink... Exactly, the series s is not a "mistake" or holding any version of the game on console or even PC back, that's what I'm saying to the person I replied to, its stupid to say that.   cursed beef Member Jan 3, 2021 998 Have to imagine MS will lift the Series S parity clause when the next consoles launch. Which will be before/around the time W4 hits, right?   Alvis Saw the truth behind the copied door Member Oct 25, 2017 12,270 EU Chronos said: This better not be a Cyberpunk situation all over again. If they can't get it to work on S, then they may just need to abandon that console. Work out a deal with MS or wait for their next generation. Click to expand... Click to shrink... ? they said that 60 FPS on Series S is challenging, not the act of releasing the game there at all. The game can simply run at 30 FPS on Series S if they can't pull off 60 FPS. Or have a 40 FPS mode in lieu of 60 FPS. The CPU and storage speed differences between last gen and current gen were gigantic. This isn't even remotely close to a comparable situation.  defaltoption Plug in a controller and enter the Konami code The Fallen Oct 27, 2017 12,485 Austin misqoute post   jroc74 Member Oct 27, 2017 34,465 defaltoption said: With that same attitude in this case you could say consoles are the mistake. You on your Series X or PS5 Pro are holding my 5090 back. Not so fun of a take anymore. Thats why its stupid. Click to expand... Click to shrink... Ah yes, clearly 5090 cards are the vast majority of the minimum requirements for PC games. How can anyone say this with a straight face anymore when there are now PC games running on a Steam Deck. At least ppl saying that about the Series S are comparing it to other consoles. That said, it is interesting they are focusing on consoles first, then PC. 
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  • Scythe Solvency Update, "Scycopter" Liquid Cooler, New $45 Air Coolers

    Coolers News Scythe Solvency Update, "Scycopter" Liquid Cooler, New Air CoolersJune 10, 2025Last Updated: 2025-06-10We looked at Scythe’s Scycopter liquid cooler, Magoroku air cooler, Big Shuriken 4, and moreThe HighlightsScythe showed off its liquid cooler, which is currently going by the working name “Scycopter”The Magoruku is a CPU cooler that’s supposed to be relatively high performing with 6x6mm heat pipes coupled with a nickel-plated copper cold plateWe talked to Scythe about the news of its European branch closing downTable of ContentsAutoTOC Grab a GN Tear-Down Toolkit to support our AD-FREE reviews and IN-DEPTH testing while also getting a high-quality, highly portable 10-piece toolkit that was custom designed for use with video cards for repasting and water block installation. Includes a portable roll bag, hook hangers for pegboards, a storage compartment, and instructional GPU disassembly cards.IntroWe visited Scythe’s booth at Computex 2025 and the company showed off several new coolers, including a mockup of a liquid cooler. Our visit comes off the heels of the news that Scythe will be closing its European branch, which we discussed with the company.Editor's note: This was originally published on May 22, 2025 as a video. This content has been adapted to written format for this article and is unchanged from the original publication.CreditsHostSteve BurkeCamera, Video EditingMike GaglioneVitalii MakhnovetsWriting, Web EditingJimmy ThangScythe Liquid CoolerTo our knowledge, we saw Scythe’s first liquid cooler at the show. We spoke with Kitagawa-san, lead designer at Scythe, who told us that he spent about the last year studying liquid coolers. The company also showed us a 3D-printed prototype peg with a piece of tape underneath it, which allows you to essentially stick it to any fan you want. A fan can then socket on top of the cooler and be angled to shoot air down toward the VRM or RAM, etc. The working name of the liquid cooler is the “Scycopter,” which is really cool and is a combination of Scythe and helicopter. Currently, the radiator thickness is pretty standard at 27mm, but that might change. The standard pump block will have an option that will allow you to install a fan on top of it. For the fins, the pitch is .1mm. That makes them pretty close together. Scythe also tells us that the total height of the copper coldplate is 1.6mm. Magoruku Grab a GN15 Large Anti-Static Modmat to celebrate our 15th Anniversary and for a high-quality PC building work surface. The Modmat features useful PC building diagrams and is anti-static conductive. Purchases directly fund our work!We showed Scythe’s Magoruku CPU cooler at last year’s Computex, but it’s coming out now. It’s supposed to be but the company tells us that it might be able to bring it down to in the US depending on market conditions. The Magoruku is supposed to be a relatively high-performing, mid-range/budget cooler. Scythe is going with a flat nickel-plated copper for its cold plate coupled with 6x6mm heat pipes. The company is using 2x120mm “Wonder Tornado” fans as Scythe calls them. They are 25mm-thick fans and use metal brackets to adjust the fan height. Mugen 6 TUFThe Mugen 6 TUF is an ASUS-themed version of the CPU cooler. Big Shuriken 4Scythe also showed off its Big Shuriken 4 CPU cooler, which the company also showed last year, but is now about final. It has cut-outs on the side of the fan, which Scythe says helps with performance as it allows air to escape from the sides. One of the things that Scythe is trying to figure out with the Big Shuriken 4 is whether to make it all black or ARGB. Scythe Closing Its European Branch Visit our Patreon page to contribute a few dollars toward this website's operationAdditionally, when you purchase through links to retailers on our site, we may earn a small affiliate commission.In regards to Scythe’s closed European branch, it sounds like the company is restructuring and moving operations to Taiwan. Scythe tells us it will still ship and sell to European customers.
    #scythe #solvency #update #quotscycopterquot #liquid
    Scythe Solvency Update, "Scycopter" Liquid Cooler, New $45 Air Coolers
    Coolers News Scythe Solvency Update, "Scycopter" Liquid Cooler, New Air CoolersJune 10, 2025Last Updated: 2025-06-10We looked at Scythe’s Scycopter liquid cooler, Magoroku air cooler, Big Shuriken 4, and moreThe HighlightsScythe showed off its liquid cooler, which is currently going by the working name “Scycopter”The Magoruku is a CPU cooler that’s supposed to be relatively high performing with 6x6mm heat pipes coupled with a nickel-plated copper cold plateWe talked to Scythe about the news of its European branch closing downTable of ContentsAutoTOC Grab a GN Tear-Down Toolkit to support our AD-FREE reviews and IN-DEPTH testing while also getting a high-quality, highly portable 10-piece toolkit that was custom designed for use with video cards for repasting and water block installation. Includes a portable roll bag, hook hangers for pegboards, a storage compartment, and instructional GPU disassembly cards.IntroWe visited Scythe’s booth at Computex 2025 and the company showed off several new coolers, including a mockup of a liquid cooler. Our visit comes off the heels of the news that Scythe will be closing its European branch, which we discussed with the company.Editor's note: This was originally published on May 22, 2025 as a video. This content has been adapted to written format for this article and is unchanged from the original publication.CreditsHostSteve BurkeCamera, Video EditingMike GaglioneVitalii MakhnovetsWriting, Web EditingJimmy ThangScythe Liquid CoolerTo our knowledge, we saw Scythe’s first liquid cooler at the show. We spoke with Kitagawa-san, lead designer at Scythe, who told us that he spent about the last year studying liquid coolers. The company also showed us a 3D-printed prototype peg with a piece of tape underneath it, which allows you to essentially stick it to any fan you want. A fan can then socket on top of the cooler and be angled to shoot air down toward the VRM or RAM, etc. The working name of the liquid cooler is the “Scycopter,” which is really cool and is a combination of Scythe and helicopter. Currently, the radiator thickness is pretty standard at 27mm, but that might change. The standard pump block will have an option that will allow you to install a fan on top of it. For the fins, the pitch is .1mm. That makes them pretty close together. Scythe also tells us that the total height of the copper coldplate is 1.6mm. Magoruku Grab a GN15 Large Anti-Static Modmat to celebrate our 15th Anniversary and for a high-quality PC building work surface. The Modmat features useful PC building diagrams and is anti-static conductive. Purchases directly fund our work!We showed Scythe’s Magoruku CPU cooler at last year’s Computex, but it’s coming out now. It’s supposed to be but the company tells us that it might be able to bring it down to in the US depending on market conditions. The Magoruku is supposed to be a relatively high-performing, mid-range/budget cooler. Scythe is going with a flat nickel-plated copper for its cold plate coupled with 6x6mm heat pipes. The company is using 2x120mm “Wonder Tornado” fans as Scythe calls them. They are 25mm-thick fans and use metal brackets to adjust the fan height. Mugen 6 TUFThe Mugen 6 TUF is an ASUS-themed version of the CPU cooler. Big Shuriken 4Scythe also showed off its Big Shuriken 4 CPU cooler, which the company also showed last year, but is now about final. It has cut-outs on the side of the fan, which Scythe says helps with performance as it allows air to escape from the sides. One of the things that Scythe is trying to figure out with the Big Shuriken 4 is whether to make it all black or ARGB. Scythe Closing Its European Branch Visit our Patreon page to contribute a few dollars toward this website's operationAdditionally, when you purchase through links to retailers on our site, we may earn a small affiliate commission.In regards to Scythe’s closed European branch, it sounds like the company is restructuring and moving operations to Taiwan. Scythe tells us it will still ship and sell to European customers. #scythe #solvency #update #quotscycopterquot #liquid
    GAMERSNEXUS.NET
    Scythe Solvency Update, "Scycopter" Liquid Cooler, New $45 Air Coolers
    Coolers News Scythe Solvency Update, "Scycopter" Liquid Cooler, New $45 Air CoolersJune 10, 2025Last Updated: 2025-06-10We looked at Scythe’s Scycopter liquid cooler, Magoroku air cooler, Big Shuriken 4, and moreThe HighlightsScythe showed off its liquid cooler, which is currently going by the working name “Scycopter”The Magoruku is a $50 CPU cooler that’s supposed to be relatively high performing with 6x6mm heat pipes coupled with a nickel-plated copper cold plateWe talked to Scythe about the news of its European branch closing downTable of ContentsAutoTOC Grab a GN Tear-Down Toolkit to support our AD-FREE reviews and IN-DEPTH testing while also getting a high-quality, highly portable 10-piece toolkit that was custom designed for use with video cards for repasting and water block installation. Includes a portable roll bag, hook hangers for pegboards, a storage compartment, and instructional GPU disassembly cards.IntroWe visited Scythe’s booth at Computex 2025 and the company showed off several new coolers, including a mockup of a liquid cooler. Our visit comes off the heels of the news that Scythe will be closing its European branch, which we discussed with the company.Editor's note: This was originally published on May 22, 2025 as a video. This content has been adapted to written format for this article and is unchanged from the original publication.CreditsHostSteve BurkeCamera, Video EditingMike GaglioneVitalii MakhnovetsWriting, Web EditingJimmy ThangScythe Liquid CoolerTo our knowledge, we saw Scythe’s first liquid cooler at the show. We spoke with Kitagawa-san, lead designer at Scythe, who told us that he spent about the last year studying liquid coolers. The company also showed us a 3D-printed prototype peg with a piece of tape underneath it, which allows you to essentially stick it to any fan you want. A fan can then socket on top of the cooler and be angled to shoot air down toward the VRM or RAM, etc. The working name of the liquid cooler is the “Scycopter,” which is really cool and is a combination of Scythe and helicopter. Currently, the radiator thickness is pretty standard at 27mm, but that might change. The standard pump block will have an option that will allow you to install a fan on top of it. For the fins, the pitch is .1mm. That makes them pretty close together. Scythe also tells us that the total height of the copper coldplate is 1.6mm. Magoruku Grab a GN15 Large Anti-Static Modmat to celebrate our 15th Anniversary and for a high-quality PC building work surface. The Modmat features useful PC building diagrams and is anti-static conductive. Purchases directly fund our work! (or consider a direct donation or a Patreon contribution!)We showed Scythe’s Magoruku CPU cooler at last year’s Computex, but it’s coming out now. It’s supposed to be $50, but the company tells us that it might be able to bring it down to $44 in the US depending on market conditions. The Magoruku is supposed to be a relatively high-performing, mid-range/budget cooler. Scythe is going with a flat nickel-plated copper for its cold plate coupled with 6x6mm heat pipes. The company is using 2x120mm “Wonder Tornado” fans as Scythe calls them. They are 25mm-thick fans and use metal brackets to adjust the fan height. Mugen 6 TUFThe Mugen 6 TUF is an ASUS-themed version of the CPU cooler. Big Shuriken 4Scythe also showed off its Big Shuriken 4 CPU cooler, which the company also showed last year, but is now about final. It has cut-outs on the side of the fan, which Scythe says helps with performance as it allows air to escape from the sides. One of the things that Scythe is trying to figure out with the Big Shuriken 4 is whether to make it all black or ARGB. Scythe Closing Its European Branch Visit our Patreon page to contribute a few dollars toward this website's operation (or consider a direct donation or buying something from our GN Store!) Additionally, when you purchase through links to retailers on our site, we may earn a small affiliate commission.In regards to Scythe’s closed European branch, it sounds like the company is restructuring and moving operations to Taiwan. Scythe tells us it will still ship and sell to European customers.
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  • Reclaiming Control: Digital Sovereignty in 2025

    Sovereignty has mattered since the invention of the nation state—defined by borders, laws, and taxes that apply within and without. While many have tried to define it, the core idea remains: nations or jurisdictions seek to stay in control, usually to the benefit of those within their borders.
    Digital sovereignty is a relatively new concept, also difficult to define but straightforward to understand. Data and applications don’t understand borders unless they are specified in policy terms, as coded into the infrastructure.
    The World Wide Web had no such restrictions at its inception. Communitarian groups such as the Electronic Frontier Foundation, service providers and hyperscalers, non-profits and businesses all embraced a model that suggested data would look after itself.
    But data won’t look after itself, for several reasons. First, data is massively out of control. We generate more of it all the time, and for at least two or three decades, most organizations haven’t fully understood their data assets. This creates inefficiency and risk—not least, widespread vulnerability to cyberattack.
    Risk is probability times impact—and right now, the probabilities have shot up. Invasions, tariffs, political tensions, and more have brought new urgency. This time last year, the idea of switching off another country’s IT systems was not on the radar. Now we’re seeing it happen—including the U.S. government blocking access to services overseas.
    Digital sovereignty isn’t just a European concern, though it is often framed as such. In South America for example, I am told that sovereignty is leading conversations with hyperscalers; in African countries, it is being stipulated in supplier agreements. Many jurisdictions are watching, assessing, and reviewing their stance on digital sovereignty.
    As the adage goes: a crisis is a problem with no time left to solve it. Digital sovereignty was a problem in waiting—but now it’s urgent. It’s gone from being an abstract ‘right to sovereignty’ to becoming a clear and present issue, in government thinking, corporate risk and how we architect and operate our computer systems.
    What does the digital sovereignty landscape look like today?
    Much has changed since this time last year. Unknowns remain, but much of what was unclear this time last year is now starting to solidify. Terminology is clearer – for example talking about classification and localisation rather than generic concepts.
    We’re seeing a shift from theory to practice. Governments and organizations are putting policies in place that simply didn’t exist before. For example, some countries are seeing “in-country” as a primary goal, whereas othersare adopting a risk-based approach based on trusted locales.
    We’re also seeing a shift in risk priorities. From a risk standpoint, the classic triad of confidentiality, integrity, and availability are at the heart of the digital sovereignty conversation. Historically, the focus has been much more on confidentiality, driven by concerns about the US Cloud Act: essentially, can foreign governments see my data?
    This year however, availability is rising in prominence, due to geopolitics and very real concerns about data accessibility in third countries. Integrity is being talked about less from a sovereignty perspective, but is no less important as a cybercrime target—ransomware and fraud being two clear and present risks.
    Thinking more broadly, digital sovereignty is not just about data, or even intellectual property, but also the brain drain. Countries don’t want all their brightest young technologists leaving university only to end up in California or some other, more attractive country. They want to keep talent at home and innovate locally, to the benefit of their own GDP.
    How Are Cloud Providers Responding?
    Hyperscalers are playing catch-up, still looking for ways to satisfy the letter of the law whilst ignoringits spirit. It’s not enough for Microsoft or AWS to say they will do everything they can to protect a jurisdiction’s data, if they are already legally obliged to do the opposite. Legislation, in this case US legislation, calls the shots—and we all know just how fragile this is right now.
    We see hyperscaler progress where they offer technology to be locally managed by a third party, rather than themselves. For example, Google’s partnership with Thales, or Microsoft with Orange, both in France. However, these are point solutions, not part of a general standard. Meanwhile, AWS’ recent announcement about creating a local entity doesn’t solve for the problem of US over-reach, which remains a core issue.
    Non-hyperscaler providers and software vendors have an increasingly significant play: Oracle and HPE offer solutions that can be deployed and managed locally for example; Broadcom/VMware and Red Hat provide technologies that locally situated, private cloud providers can host. Digital sovereignty is thus a catalyst for a redistribution of “cloud spend” across a broader pool of players.
    What Can Enterprise Organizations Do About It?
    First, see digital sovereignty as a core element of data and application strategy. For a nation, sovereignty means having solid borders, control over IP, GDP, and so on. That’s the goal for corporations as well—control, self-determination, and resilience.
    If sovereignty isn’t seen as an element of strategy, it gets pushed down into the implementation layer, leading to inefficient architectures and duplicated effort. Far better to decide up front what data, applications and processes need to be treated as sovereign, and defining an architecture to support that.
    This sets the scene for making informed provisioning decisions. Your organization may have made some big bets on key vendors or hyperscalers, but multi-platform thinking increasingly dominates: multiple public and private cloud providers, with integrated operations and management. Sovereign cloud becomes one element of a well-structured multi-platform architecture.
    It is not cost-neutral to deliver on sovereignty, but the overall business value should be tangible. A sovereignty initiative should bring clear advantages, not just for itself, but through the benefits that come with better control, visibility, and efficiency.
    Knowing where your data is, understanding which data matters, managing it efficiently so you’re not duplicating or fragmenting it across systems—these are valuable outcomes. In addition, ignoring these questions can lead to non-compliance or be outright illegal. Even if we don’t use terms like ‘sovereignty’, organizations need a handle on their information estate.
    Organizations shouldn’t be thinking everything cloud-based needs to be sovereign, but should be building strategies and policies based on data classification, prioritization and risk. Build that picture and you can solve for the highest-priority items first—the data with the strongest classification and greatest risk. That process alone takes care of 80–90% of the problem space, avoiding making sovereignty another problem whilst solving nothing.
    Where to start? Look after your own organization first
    Sovereignty and systems thinking go hand in hand: it’s all about scope. In enterprise architecture or business design, the biggest mistake is boiling the ocean—trying to solve everything at once.
    Instead, focus on your own sovereignty. Worry about your own organization, your own jurisdiction. Know where your own borders are. Understand who your customers are, and what their requirements are. For example, if you’re a manufacturer selling into specific countries—what do those countries require? Solve for that, not for everything else. Don’t try to plan for every possible future scenario.
    Focus on what you have, what you’re responsible for, and what you need to address right now. Classify and prioritise your data assets based on real-world risk. Do that, and you’re already more than halfway toward solving digital sovereignty—with all the efficiency, control, and compliance benefits that come with it.
    Digital sovereignty isn’t just regulatory, but strategic. Organizations that act now can reduce risk, improve operational clarity, and prepare for a future based on trust, compliance, and resilience.
    The post Reclaiming Control: Digital Sovereignty in 2025 appeared first on Gigaom.
    #reclaiming #control #digital #sovereignty
    Reclaiming Control: Digital Sovereignty in 2025
    Sovereignty has mattered since the invention of the nation state—defined by borders, laws, and taxes that apply within and without. While many have tried to define it, the core idea remains: nations or jurisdictions seek to stay in control, usually to the benefit of those within their borders. Digital sovereignty is a relatively new concept, also difficult to define but straightforward to understand. Data and applications don’t understand borders unless they are specified in policy terms, as coded into the infrastructure. The World Wide Web had no such restrictions at its inception. Communitarian groups such as the Electronic Frontier Foundation, service providers and hyperscalers, non-profits and businesses all embraced a model that suggested data would look after itself. But data won’t look after itself, for several reasons. First, data is massively out of control. We generate more of it all the time, and for at least two or three decades, most organizations haven’t fully understood their data assets. This creates inefficiency and risk—not least, widespread vulnerability to cyberattack. Risk is probability times impact—and right now, the probabilities have shot up. Invasions, tariffs, political tensions, and more have brought new urgency. This time last year, the idea of switching off another country’s IT systems was not on the radar. Now we’re seeing it happen—including the U.S. government blocking access to services overseas. Digital sovereignty isn’t just a European concern, though it is often framed as such. In South America for example, I am told that sovereignty is leading conversations with hyperscalers; in African countries, it is being stipulated in supplier agreements. Many jurisdictions are watching, assessing, and reviewing their stance on digital sovereignty. As the adage goes: a crisis is a problem with no time left to solve it. Digital sovereignty was a problem in waiting—but now it’s urgent. It’s gone from being an abstract ‘right to sovereignty’ to becoming a clear and present issue, in government thinking, corporate risk and how we architect and operate our computer systems. What does the digital sovereignty landscape look like today? Much has changed since this time last year. Unknowns remain, but much of what was unclear this time last year is now starting to solidify. Terminology is clearer – for example talking about classification and localisation rather than generic concepts. We’re seeing a shift from theory to practice. Governments and organizations are putting policies in place that simply didn’t exist before. For example, some countries are seeing “in-country” as a primary goal, whereas othersare adopting a risk-based approach based on trusted locales. We’re also seeing a shift in risk priorities. From a risk standpoint, the classic triad of confidentiality, integrity, and availability are at the heart of the digital sovereignty conversation. Historically, the focus has been much more on confidentiality, driven by concerns about the US Cloud Act: essentially, can foreign governments see my data? This year however, availability is rising in prominence, due to geopolitics and very real concerns about data accessibility in third countries. Integrity is being talked about less from a sovereignty perspective, but is no less important as a cybercrime target—ransomware and fraud being two clear and present risks. Thinking more broadly, digital sovereignty is not just about data, or even intellectual property, but also the brain drain. Countries don’t want all their brightest young technologists leaving university only to end up in California or some other, more attractive country. They want to keep talent at home and innovate locally, to the benefit of their own GDP. How Are Cloud Providers Responding? Hyperscalers are playing catch-up, still looking for ways to satisfy the letter of the law whilst ignoringits spirit. It’s not enough for Microsoft or AWS to say they will do everything they can to protect a jurisdiction’s data, if they are already legally obliged to do the opposite. Legislation, in this case US legislation, calls the shots—and we all know just how fragile this is right now. We see hyperscaler progress where they offer technology to be locally managed by a third party, rather than themselves. For example, Google’s partnership with Thales, or Microsoft with Orange, both in France. However, these are point solutions, not part of a general standard. Meanwhile, AWS’ recent announcement about creating a local entity doesn’t solve for the problem of US over-reach, which remains a core issue. Non-hyperscaler providers and software vendors have an increasingly significant play: Oracle and HPE offer solutions that can be deployed and managed locally for example; Broadcom/VMware and Red Hat provide technologies that locally situated, private cloud providers can host. Digital sovereignty is thus a catalyst for a redistribution of “cloud spend” across a broader pool of players. What Can Enterprise Organizations Do About It? First, see digital sovereignty as a core element of data and application strategy. For a nation, sovereignty means having solid borders, control over IP, GDP, and so on. That’s the goal for corporations as well—control, self-determination, and resilience. If sovereignty isn’t seen as an element of strategy, it gets pushed down into the implementation layer, leading to inefficient architectures and duplicated effort. Far better to decide up front what data, applications and processes need to be treated as sovereign, and defining an architecture to support that. This sets the scene for making informed provisioning decisions. Your organization may have made some big bets on key vendors or hyperscalers, but multi-platform thinking increasingly dominates: multiple public and private cloud providers, with integrated operations and management. Sovereign cloud becomes one element of a well-structured multi-platform architecture. It is not cost-neutral to deliver on sovereignty, but the overall business value should be tangible. A sovereignty initiative should bring clear advantages, not just for itself, but through the benefits that come with better control, visibility, and efficiency. Knowing where your data is, understanding which data matters, managing it efficiently so you’re not duplicating or fragmenting it across systems—these are valuable outcomes. In addition, ignoring these questions can lead to non-compliance or be outright illegal. Even if we don’t use terms like ‘sovereignty’, organizations need a handle on their information estate. Organizations shouldn’t be thinking everything cloud-based needs to be sovereign, but should be building strategies and policies based on data classification, prioritization and risk. Build that picture and you can solve for the highest-priority items first—the data with the strongest classification and greatest risk. That process alone takes care of 80–90% of the problem space, avoiding making sovereignty another problem whilst solving nothing. Where to start? Look after your own organization first Sovereignty and systems thinking go hand in hand: it’s all about scope. In enterprise architecture or business design, the biggest mistake is boiling the ocean—trying to solve everything at once. Instead, focus on your own sovereignty. Worry about your own organization, your own jurisdiction. Know where your own borders are. Understand who your customers are, and what their requirements are. For example, if you’re a manufacturer selling into specific countries—what do those countries require? Solve for that, not for everything else. Don’t try to plan for every possible future scenario. Focus on what you have, what you’re responsible for, and what you need to address right now. Classify and prioritise your data assets based on real-world risk. Do that, and you’re already more than halfway toward solving digital sovereignty—with all the efficiency, control, and compliance benefits that come with it. Digital sovereignty isn’t just regulatory, but strategic. Organizations that act now can reduce risk, improve operational clarity, and prepare for a future based on trust, compliance, and resilience. The post Reclaiming Control: Digital Sovereignty in 2025 appeared first on Gigaom. #reclaiming #control #digital #sovereignty
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    Reclaiming Control: Digital Sovereignty in 2025
    Sovereignty has mattered since the invention of the nation state—defined by borders, laws, and taxes that apply within and without. While many have tried to define it, the core idea remains: nations or jurisdictions seek to stay in control, usually to the benefit of those within their borders. Digital sovereignty is a relatively new concept, also difficult to define but straightforward to understand. Data and applications don’t understand borders unless they are specified in policy terms, as coded into the infrastructure. The World Wide Web had no such restrictions at its inception. Communitarian groups such as the Electronic Frontier Foundation, service providers and hyperscalers, non-profits and businesses all embraced a model that suggested data would look after itself. But data won’t look after itself, for several reasons. First, data is massively out of control. We generate more of it all the time, and for at least two or three decades (according to historical surveys I’ve run), most organizations haven’t fully understood their data assets. This creates inefficiency and risk—not least, widespread vulnerability to cyberattack. Risk is probability times impact—and right now, the probabilities have shot up. Invasions, tariffs, political tensions, and more have brought new urgency. This time last year, the idea of switching off another country’s IT systems was not on the radar. Now we’re seeing it happen—including the U.S. government blocking access to services overseas. Digital sovereignty isn’t just a European concern, though it is often framed as such. In South America for example, I am told that sovereignty is leading conversations with hyperscalers; in African countries, it is being stipulated in supplier agreements. Many jurisdictions are watching, assessing, and reviewing their stance on digital sovereignty. As the adage goes: a crisis is a problem with no time left to solve it. Digital sovereignty was a problem in waiting—but now it’s urgent. It’s gone from being an abstract ‘right to sovereignty’ to becoming a clear and present issue, in government thinking, corporate risk and how we architect and operate our computer systems. What does the digital sovereignty landscape look like today? Much has changed since this time last year. Unknowns remain, but much of what was unclear this time last year is now starting to solidify. Terminology is clearer – for example talking about classification and localisation rather than generic concepts. We’re seeing a shift from theory to practice. Governments and organizations are putting policies in place that simply didn’t exist before. For example, some countries are seeing “in-country” as a primary goal, whereas others (the UK included) are adopting a risk-based approach based on trusted locales. We’re also seeing a shift in risk priorities. From a risk standpoint, the classic triad of confidentiality, integrity, and availability are at the heart of the digital sovereignty conversation. Historically, the focus has been much more on confidentiality, driven by concerns about the US Cloud Act: essentially, can foreign governments see my data? This year however, availability is rising in prominence, due to geopolitics and very real concerns about data accessibility in third countries. Integrity is being talked about less from a sovereignty perspective, but is no less important as a cybercrime target—ransomware and fraud being two clear and present risks. Thinking more broadly, digital sovereignty is not just about data, or even intellectual property, but also the brain drain. Countries don’t want all their brightest young technologists leaving university only to end up in California or some other, more attractive country. They want to keep talent at home and innovate locally, to the benefit of their own GDP. How Are Cloud Providers Responding? Hyperscalers are playing catch-up, still looking for ways to satisfy the letter of the law whilst ignoring (in the French sense) its spirit. It’s not enough for Microsoft or AWS to say they will do everything they can to protect a jurisdiction’s data, if they are already legally obliged to do the opposite. Legislation, in this case US legislation, calls the shots—and we all know just how fragile this is right now. We see hyperscaler progress where they offer technology to be locally managed by a third party, rather than themselves. For example, Google’s partnership with Thales, or Microsoft with Orange, both in France (Microsoft has similar in Germany). However, these are point solutions, not part of a general standard. Meanwhile, AWS’ recent announcement about creating a local entity doesn’t solve for the problem of US over-reach, which remains a core issue. Non-hyperscaler providers and software vendors have an increasingly significant play: Oracle and HPE offer solutions that can be deployed and managed locally for example; Broadcom/VMware and Red Hat provide technologies that locally situated, private cloud providers can host. Digital sovereignty is thus a catalyst for a redistribution of “cloud spend” across a broader pool of players. What Can Enterprise Organizations Do About It? First, see digital sovereignty as a core element of data and application strategy. For a nation, sovereignty means having solid borders, control over IP, GDP, and so on. That’s the goal for corporations as well—control, self-determination, and resilience. If sovereignty isn’t seen as an element of strategy, it gets pushed down into the implementation layer, leading to inefficient architectures and duplicated effort. Far better to decide up front what data, applications and processes need to be treated as sovereign, and defining an architecture to support that. This sets the scene for making informed provisioning decisions. Your organization may have made some big bets on key vendors or hyperscalers, but multi-platform thinking increasingly dominates: multiple public and private cloud providers, with integrated operations and management. Sovereign cloud becomes one element of a well-structured multi-platform architecture. It is not cost-neutral to deliver on sovereignty, but the overall business value should be tangible. A sovereignty initiative should bring clear advantages, not just for itself, but through the benefits that come with better control, visibility, and efficiency. Knowing where your data is, understanding which data matters, managing it efficiently so you’re not duplicating or fragmenting it across systems—these are valuable outcomes. In addition, ignoring these questions can lead to non-compliance or be outright illegal. Even if we don’t use terms like ‘sovereignty’, organizations need a handle on their information estate. Organizations shouldn’t be thinking everything cloud-based needs to be sovereign, but should be building strategies and policies based on data classification, prioritization and risk. Build that picture and you can solve for the highest-priority items first—the data with the strongest classification and greatest risk. That process alone takes care of 80–90% of the problem space, avoiding making sovereignty another problem whilst solving nothing. Where to start? Look after your own organization first Sovereignty and systems thinking go hand in hand: it’s all about scope. In enterprise architecture or business design, the biggest mistake is boiling the ocean—trying to solve everything at once. Instead, focus on your own sovereignty. Worry about your own organization, your own jurisdiction. Know where your own borders are. Understand who your customers are, and what their requirements are. For example, if you’re a manufacturer selling into specific countries—what do those countries require? Solve for that, not for everything else. Don’t try to plan for every possible future scenario. Focus on what you have, what you’re responsible for, and what you need to address right now. Classify and prioritise your data assets based on real-world risk. Do that, and you’re already more than halfway toward solving digital sovereignty—with all the efficiency, control, and compliance benefits that come with it. Digital sovereignty isn’t just regulatory, but strategic. Organizations that act now can reduce risk, improve operational clarity, and prepare for a future based on trust, compliance, and resilience. The post Reclaiming Control: Digital Sovereignty in 2025 appeared first on Gigaom.
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  • How AI is reshaping the future of healthcare and medical research

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