1 2 3 1 2 3. Does that sound right? We're going to do all that personal drama in 90 minutes.
Oh, yeah. Oh, don't worry. Talk about building super intelligence. Is this part all going to be in the podcast?
No. Well, maybe not. Bear with me through my slightly silly intro, but uh...
I think you guys are going to be okay.
Welcome to the fortress of finance, the capital of capital. This is not that podcast. This is Core Memory. I am Ashley Vance.
And I'm Kylie Robinson, and I think we have a hell of an episode for you. Normally, we do an introduction of people at this part, but that's perhaps unnecessary. Today we have Sam Altman and Greg Brockman, the co-founders of OpenAI. You may have heard of it. Thank you guys for being here.
I think this is the first time you guys have ever done a podcast together.
That is amazing. But I think that's true. Certainly in a long time.
And I will not fight you for doing it on our show, but you did buy a podcast. Is there? We just locked out.
Yeah, I'll take it. I'll take it. I was curious why you guys bought a podcast. It's not really... We don't have to go deep on it, but did you have quick thoughts on that?
I think the people who do TBPN are incredible. I think they're just very creative thinkers. And I think that in this world that we're moving to of building these AI systems that are so useful for people and helping people understand why that's valuable for them in their personal lives and work lives, like these are the kinds of people that I think could help tell that message.
I see you on it. Have you been on TBPN?
Yeah. Okay. Okay. Um I don't watch all the episodes, but it's a fun pod. Um well, I thought, you know, since this is you guys, we haven't done this together at least in a while, we would... I was going to go down nostalgia lane just for a little bit at the beginning. Um Kylie and I have gotten to know both of you over the years. Uh you know, I was just... I we were reflecting as we were preparing for this. We're a little bit past the 10-year anniversary. You guys are two of the remaining co-founders. I think Wojciech is the third. So you're, you know, you're this constant line that's been running through the company. You started as an underdog. You ended up as the top dog. It's all through a lot of drama, undulations. Um I was... I mean I was genuinely curious how your relationship through all this has changed and how you guys have played off each other and if it's morphed over time.
It is extremely nice... and look, we all wish there were less drama and we wish we just got to focus on the tech. But in a world of so much chaos and drama and you know tension and fighting and power struggles, it has been unbelievably nice to have a relationship with someone that's got the full context. We have all this history and to really depend on each other in amazing times, very tough times. Uh it has been one of the nicest things about all of OpenAI. You know, in many ways, the very first moment of OpenAI was right after this dinner that we did in July of 2015, and Sam and I were driving back to the city together and we looked at each other and we were like, we have to do this, right? There've been all this conversation of is it too late to start a lab that could go after AGI and have a positive impact?
That seems so ridiculous now that we were so worried about that, but it was too late.
Yeah, you missed it. You missed it. I remember feeling like that when you guys started though. I was like, 'No, they're going to run away with this,' you know.
And you know, the conclusion for dinner was it wasn't obviously impossible. And I think both of us just felt like, 'Okay, this is just so important. We just have to do it.' And I think that spirit continues. And a lot of how we operated in the early days. Like I remember I was unemployed at the time, so I was full-time on it the next day. Sam actually had a day job. Um, but we were constantly on the phone like probably like five times a day.
Were you guys already... were you like close friends already at that point or not?
We had known each other for a super long time or it felt like a super... I don't actually...
Yeah. 2010, 2011, whenever you started at Stripe.
That's right. Yes. So we met through the Collisons. And so we'd been kind of casual social friends.
I guess it wasn't as long as I thought. Yeah. Maybe it was 2010 and this was now 2015. So five years.
Time compresses. Yeah. And and and obviously I mean the being in the pressure cooker of all this doing this work I mean I would imagine it only... you guys have only got closer over time.
Yeah. You know people use the word trauma bonding. I hate that. I've... I like the other things about like the people you're in the foxhole with. The one of the nice things about hard work no matter what, but certainly hard work in stressful times is you really like forge these relationships that I at least have not seen get formed any other way.
Yeah. And I do think the way that Sam and I work and relate is maybe different from what you'd expect from a typical co-founder relationship. Like I think that we are just in constant contact. That five calls a day, two minutes, five minutes each, that kind of spirit remains. Like I think we're just in constant sync and we don't always agree on everything, right? It's not like we come at the world from exactly the same point of view. But that's why we're so strong together, right? Is that I think we have very complementary approaches that Sam will say here's an idea. I'll think about well maybe we could do it this other way or what about if we approached it with this angle or how does this relate to this other thing that we're thinking about. And one thing I deeply appreciate about Sam is that I think he always sees these connections between different ideas or just like keeps focused on here's the big picture that we need to get to and then together we figure out well how do we actually do it and I think connecting the grand ambition with the execution like that is what has always distinguished OpenAI.
Yeah. What are some of the points in these 10 years where you felt like it was really important that you guys diverge? Do you remember any key moments for you guys?
I think one of the things that Greg has done the best, which is not my instinct, is really just push to focus on the most important thing in his own work and also in what the company's going to do. Um so there have been times where I have wanted to do more things and Greg has just said, you know, is this the most important thing? Let's really just do this. Let's get the company focused. And we've diverged on that and that's been like a very helpful spirit of Greg's throughout the company.
Yeah. And I would also add I think even for example thinking about compute and just constantly raising the ambition and sometimes I feel like okay I kind of logically know that yes like we're moving to this compute powered economy and yes that demand is always going to outstrip supply but like we've got all this hard work to do and we already have all these big computers and we're operationalizing them and you know you still have all this just physical infrastructure to build and you feel already swarmed in it and swamped in it and Sam is like no we need even more. And I think that that actually has been a very important thing to really not like sometimes it's easy to lose sight of the high order bit of just the fact of this is going to be so important for not just the next 6 months but this is what's important for the next 2 years the next 5 years 10 years and I think that the keep... like you need this balance of sometimes swimming in the details but you can't be swamped in the details and I think that that balance is something that I think again is what really has contributed to what OpenAI is and where we are going to go.
Is there... there must be one product or strategy you guys have... what's the one that you've disagreed about the most vehemently?
I was just thinking when Greg was talking about this... this is not a product but it was the thing that came to mind is that I was going to say even before you asked that we used to talk a lot about how to talk about safety. We never disagreed on the extreme importance of safety and what it will mean to get this right or get this wrong. But the field has had a strange relationship with how we've talked about safety, how we've used safety, how much that becomes about power versus actually keeping things safe. And I think earlier in our history, I got swept up more in the we got to really talk about this in a particular frame. And Greg was very disciplined about we're not going to fall into the traditional frame. We can't talk about that way. Now even then I think we have because this is so important... I would ever have fallen into the trap of still talking more in the wrong frame than we should. But I think one of OpenAI's greatest contributions to date has been finding a different way to talk about safety. Not just in how we build the products and how we talk about society needs to do but like how we deploy them. The whole idea of iterative deployment... getting to a world where we're figuring out how to deploy products that get increasingly safe as the stakes go up. Greg really held a line there that I think has been quite important to the company against extreme pressure not to do that and I think that's been quite important to our whole strategy not just how we talk about things but how we ship and build products.
Yeah. And if you look at for example the OpenAI Foundation which is the nonprofit that governs OpenAI and has a very large chunk of equity. One of its pillars is AI resilience. And what that really means is thinking about how do we make AI be something positive for the world. And the answer is not any one intervention, right? It's not you have chain of thought monitoring and now you've achieved the mission. It's really a whole deep sequence of different ways that society should orient around this technology. And I think that this perspective of you're not going to solve AGI going well for the world in a paper, it has to be a worldwide effort from contributions from society, from many different people, from many different ways of really understanding what this technology is, how it will affect people, how it will affect the world. And this is something that was not I think at all appreciated or understood when we were starting out 10 years ago because it's very easy just to fixate on you know we're technologists we're building technology that's the only problem we need to solve and I'm not saying anyone explicitly said it that way but I think sometimes you can fall into a mental trap of thinking about it that way and so a lot of what I think we have spent time on is being first principles thinkers and really thinking about how do you operationally deliver transformative technology to the world in a way that is going to actually help people in their daily lives. And one thing you realize is, well, if you have a very powerful piece of technology that will change things, probably it's going to go better if you've had a less powerful piece of technology, you've already helped change things in a positive way. And so, if you just think about it that way, you start to really be pulled down this road of thinking about resilience, thinking about iterative deployment. And again, I think this is a lot of the dynamic within OpenAI between the two of us that we're always thinking about these questions of how do we actually achieve this mission and make it go better.
Yeah, it feels like just yesterday I saw you at South by 2022, 2023 and it was a completely different discussion about AI than what we hear today. And it feels like that's something that's changed in 10 years if like how you discuss safety and alignment. And I'm wondering how you reflect on that now. Like what would you have changed in those panels and those news hits and like what have you learned about talking about safety?
Even before we get to safety, I think we have fallen in the frame as tech nerds of talking about we're going to build super intelligence and dot dot dot it's going to be great for you and we've not filled in enough of the dot dot dot. Like we talk about we're building this amazing technology it's going to do all these wonderful things. And there is like a sense in the world now of okay looks like you were right you are going to build this thing. Um why do we want that? What's that going to do for us? And the thing that a lot of the field has said of oh it's going to cure cancer and you'll be so happy or like that's clearly not quite resonating. A lot of people are like sure cure cancer that'd be wonderful. Um, I think what people really want is prosperity, agency, that they're going to continue to have meaningful work to do. Um, there I saw an incredible post the other day that really stuck with me, which was like a right to adversity. People actually, you want some challenges in life. You don't want every day to be perfect and everything done for you. And there's a fear with AI that like let's say you're right. Let's say you build it. Let's say it makes all this money and does all the work and whatever. Like what do I do? What's my kid going to do? What's life going to be like? Where's the growth going to come from? What are people going to strive for? Um, and I think we've talked as a field and as OpenAI and as Greg and I, we've talked a lot about the amazing technology and what it can do and what it like the technological marvel and we have not connected the dots enough on here is what the future's going to be like. Here is, you know, when I talk to parents with kind of school age kids, the most common question is like, 'What should my kids study? What's the future going to be like? What will still have economic value?' And I realize that that's not quite the question they're really trying to ask. It's like, 'How is my kid going to have a fulfilling life in this new world?' You know, you can answer it economically if you want, but that doesn't actually settle people. And I think it's because there's a deeper thing here.
I was just going to say and I think we actually have a lot of perspective on this and I think that for example within ChatGPT we have so many people who say that my life or the life of a loved one was saved through information I got through ChatGPT, right? Whether it's there's someone who had a kid who had blinding headaches they were denied an MRI they used ChatGPT to try to research the symptoms and used to argue to be able to get insurance for the MRI. Turned out it was a brain tumor. They were able to intervene and save his life and just navigating that experience that family says we have no idea how we would do this without ChatGPT. And that's just one story. There are so many of those. I think people really understanding that this technology can help not just abstractly society but can help them, right? It can help them make money. Right now we're starting to see this wave of entrepreneurship. I think that's going to be a huge theme throughout this year. And I think we have a lot of perspective on well, we're going to build these AIs that are able to make rather than you contort yourself to the computer, right? You think about the way we do work. It's not natural, right? It's not kind of what we were designed to do. Um, and instead the computer is going to do work for you. And the question of well, what is the work? What is good? Like what is the thing that you actually want to be done? That's going to be something very deeply human, right? This agency, this empowerment. And so I think there is this very optimistic and not blindly optimistic, but I think this very positive change that this technology is bringing right now, but it's so much easier to just notice what's going to go away. Like what is the thing that you thought was solid and stable that's going to change, but it's much harder to see, well, what's coming? Like what's the new thing that you get? What is the benefit that comes as a part of this transformation? I think that's something that we're increasingly realizing that we also have to really spell out in addition to spelling out the other sides of it.
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I have a couple questions based off what both of you were saying. Um so I just went to Oberlin College with my son and we were in this room with I don't know 600, 700 people and it was fascinating to... I mean, it's in Ohio and people had come from all over the country and the president was up there giving a talk and then opened it up to Q&A and so many of the questions were about AI, but they were... it reinforced for me that how much of a bubble we live in here because they were what I would consider... I mean it's not trying to like put anyone down. They were pretty basic questions. I just... my overwhelming sense of the room was like, 'Wow, you guys kind of like don't know what's unfolding and about to come across all of you.' And I don't know, it wasn't... I don't know it was like alarming. It was just eye opening for me, you know, and they were asking... they were obviously asking stuff about like, well, how are you going to use AI in class? How are you going to stop kids from just relying on it? But then it was like, you know, they kind of advanced a little bit beyond there. That I felt like this room of pretty smart people were not really in touch with what's going on. So I mean if this is a problem that people don't know these examples of what could be done and we don't even know what shape this could take exactly that you just... I don't see how we solve this and sort of prepare people in some way.
I do have one sort of positive take on this which is that I think that if you just read about AI it gives you one impression right? It's again it's like very... it just feels like you're trying to wrap your mind around this new technology what is it but when you use it it's so intuitive right? And that is the purpose of AI in many ways. It's like you think about back to how we've designed computers for the past 70 years it's really about the machine doesn't quite get you right? It's like you have these goals in your head you have to break it down into the machine's language whether that's writing assembly code or okay fine now we get higher level languages now you can kind of talk to your computer but even if you think about how ChatGPT works you still have to really understand concepts of language models right? The fact like why do you have to create new conversations right? New tabs like why can't it just be a thing you talk to that remembers everything right? There's these limitations that are technological limitations but we're improving them and so I think that what we're building is the most intuitive technology. We are building something that can talk the machine to you. And when people use it, they've realized, wow, this is what I can do with it. Like some of the stories that I love hearing are someone in the Midwest who, you know, one of my friends is who his sister was telling him about this app that she wanted to see someone she wish someone had created. She described in a detailed way. While he was listening, he was like, 'Uh-huh. Uh-huh.' Typing into Codex exactly what she was saying. Pushed enter. Few hours later, he shows her the result. It's an app that's exactly what she described. And she's like, what the hell is this? Who built this? Like, this is exactly what I wanted. And he said, you built it. Right. And that is that kind of aha moment that I think that everyone is going to go through. And once you experience what AI can do for you and the fact that you are now empowered like you have an image in your head you want to see in the world. If you look at some of the upcoming... some of the new image models we have absolutely incredible like you can create in a way that was never possible before and the fact that if you're like... like another story that I think about so my grandmother had dementia, Alzheimer's and that it was extremely tough for everyone. But one thing that really stuck out to me was she was actually able to use her Alexa to play music and she could still remember the lyrics and sing along to songs. And it was just a way that she was connected to who she was through technology. And that really stood out to me. It's like if you can build interfaces that are intuitive that anyone can connect to them in ways that right now it feels like we have pieces of technology that are targeted to specific individuals or that you have to build all this skill that's not really related to deeply what you want but is just somehow specific to the tech itself.
Three things came up for me during what Greg was saying um which I agree with all of. One before we launched we used to try to talk to people and say this AI thing is coming you got to pay attention it's going to change everything it's really important and it got kind of no attention. We wrote these beautiful blog posts we sort of did all these incredibly impressive feats we won video game competitions we had a robot that could do a Rubik's cube with a hand we did all this amazing stuff and we kind of felt pretty cool and we kind of said, 'Oh, you know, the New York Times wrote about this. We must be doing great.' But really truly no one cared. It got no actual impact. And then we launched ChatGPT, which was by far not the most impressive technological thing we had done by far. By far. And as soon as people could feel it, they're like, 'Okay, I understand it.' I think that was the moment probably most that the world has said, 'Maybe this AI thing is real.' like collectively all at once because people can use it and they can get value out of it. They can develop their own sense. It's very different than hearing about it. That's happened again as Greg said with coding models. Um but those have really been the two kind of like large significant moments where I think the world has updated and said okay there's this thing happening. There will be more in the future, but so far the fact that you can ask a computer anything and get an answer or have a computer do anything with code for you. Um those have been really powerful and I think that's how the world's going to update. Us saying super intelligence is coming is going to change everything. You know, maybe the people that listen to this podcast will sort of say, 'All right, sounds reasonable. Probably should pay attention to that.' But it won't have that big impact on the world. Uh so I think the most important thing we can do to help that audience that people think not just about like what does this mean for people not cheating in class but like what is this going to mean for the world is to ship great delightful products that create a lot of value and are easy for people to use and we will continue to do that. The second thing is we have seen again and again in our history that when we put something out that's pretty good people say I can't really imagine what happens if this gets better. It can't get much better. This image model that Greg was mentioning, which we'll launch soon, was a real example of that for me. I kind of roughly thought image generation was solved. I was like, it's really good. Like, I don't need it to get any better. And then this new thing has been a real reminder of like, wow, this can go so much further and there's so much more I can do.
It makes ridiculously great images.
Has all text? Because I try to make Core Memory merch mockups.
Try again very soon. Um, great job. The team really did a great job with this one. But even with ChatGPT, like when we put GPT-4 in ChatGPT, I remember a lot of people like sophisticated friends of mine saying, 'This is it. This is AGI. Like if the model got smarter, I don't care. Just make it cheaper. Like I can't. This is amazing.' Um, and if you go back and use that whatever it was, I guess like March of 2023 version of GPT-4, you'll be like, 'This was terrible.' But at the time, people were like, 'It's solved. It's solved.' I mean it's beat the Turing test. It's done. It can't get any better. And then it gets better and better and you can just keep raising the expectations and possibility of what you can do to say nothing of then you get into reasoning models and do code. I'm just talking about how much better ChatGPT got in that time period. So I think we see this again and again too where the world is like okay you made this amazing thing that's as good as it's going to get. That's as good as I need. And then month by month or at least quarter by quarter expectations and ability ratchet up in a huge way. And then the third thing that Greg was saying there is these models are still quite dumb relative to what they will be but more than that they have quite limited awareness of your life. You are still having to like massage them and cajole them and try to get the thing that you want. Uh we are not... no longer that far away from a model that just knows all of your context. It knows about you. It knows about your life. It knows what you're doing. It knows what you care about. It knows about the people in your life. It has access to your computer and your browser and if you want, of course, in the ways you want. It has access maybe increasingly over time to what's happening in the real world around you. That is going to be a complete change to what it feels like to use a computer and what it feels like to use AI. And I am tremendously excited about that. But I don't think even we have a good intuition yet for what that's really going to feel like.
To that point, yeah, you think about how much time you spend right now just explaining to Chat or whatever tool you're using what's going on. And think of how frustrating that is. Like if it's like you had a coworker, you're constantly trying to explain to them, no, this is kind of what I want. This is what's going on. There's context I could package like that. Exactly. Right. Like it's just not really how you want these systems to behave. And just to say one more thing on what Sam was saying is that I think that one of the biggest technical challenges we have at OpenAI is too much opportunity. Like AI is this field of boundless opportunity. No matter what dimension you expand on, there's going to be something new and unprecedented and amazing. And so the important thing is having a vision for where can we really focus where we're going to get the most returns and the most benefit from this, you know, having multiple different efforts that all add up to something. And I think that when it comes to we have these coding systems now, but I think it's going to clearly expand to just all computer work. And it's funny by the way that you know you think about just the degree to which you have all of this like the work that you do it's like very seamlessly interlinked between you're having in-person conversation you're typing this on your computer and trying to really figure out how to get the context in there it's going to be such an important problem all these things matter but then also in your personal life you really want this and we're starting to call where we want to go the personal AGI right this AI that really knows you has the context that you can trust it right that you ask it questions related to finances or health and it can give you trustworthy information. All these things are important and it needs that context as well. And so you start to really see that there's this blurry line between an AI that's used for this deep computer work and an AI that's used in your personal life at a technological level. Even if you want different systems because you want one that really just knows your work context, one that knows your personal context. And so you can pursue those in parallel and build on the same technological foundations. And the thing that I find most amazing about the technology we're building on is it's all at the core one neural net, right? It's still deep learning. You're scaling it up. You're building one system and you're applying it to all these different amazing applications.
Can I ask a... I want to ask a question sort of along those lines. I mean, I promised myself I wouldn't do this to you. Um, but I mean I was kind of like... I wasn't like a non-believer, but I could see AI doing incredible things, but I was kind of skeptical until relatively recently on... what updated you?
Well, a couple things. I mean, one was I started playing with agents a lot more and really shaping them to do what I wanted and kind of feeling what both of you were talking about. It's like, oh, this is actually saving me a lot of time. It's doing my bidding. It's doing it quite well. And the other is, you know, I cover biotech so much and just seeing some of the results that are coming out is... it strikes me that like coding and biotech seem like the most obvious places right now where it's really going. But then, you know, I was reading... I was talking to you the other day at dinner and reading some of the things that you've written about, you know, I see this clear path based off LLM to going to what you describe. I still have this part of me though. I think it's because I deal in language so much where the writing is still not great where I... this is nothing other than like anecdotal and intuitive is just it strikes me that the feeling I get back still is like no this is not super intelligence.
We are not there yet on personality.
But like does LLM get you there?
LLMs will get us there. I would just think of it as it's very jagged. Right. And I mean it's okay. For example, just in the past couple days, o1 solved this long-standing problem. Uh so this mathematical mystery that's been of great interest for a long time. A mathematician who spent a lot of time working on this many years thinking about this problem posted about his views of what the contribution was. Terence Tao also is saying that this looks like there's like maybe a connection between different fields of mathematics that this AI has discovered and we're starting to see real beauty come out of these machines. Now that's a particular domain, right? Mathematics is very different from creative writing and I think that the fact of these AIs being able to have interesting insights and being able to help... there's so much that these mathematicians are now saying well think about what more we can do. And so I think that we have a jagged frontier in terms of what these AIs are good at. We know how to keep pushing that frontier back. But I think that the thing that we're really looking for if you think about AlphaGo move 37, right? That was something that not just it was this deep insight, but it really changed people's understanding of the game of Go and more people play Go now, right? So that it really increased the meaning of what people were doing. And so I think that what we're going to do is we're going to make something that is going to... you'll have fewer complaints about it. But I think you're also going to be just way more able to do the thing that you want in writing than you can imagine today.
I'm sorry to harp on this, but I was told GPT-5 was going to be really good at writing. And my like update when I became less cynical was reasoning models. And when Claude delivered like really good research and then you guys had a research feature that was for me like oh my god this is amazing cuz it saved me a lot of time but I was promised before that I would have good writing by now. The writing feels... there's no soul, you know, there's something missing.
Well I'll tell you so from a technical perspective the technology we have is you can train a model in this unsupervised way right? So it really we look at all the publicly available data and it learns to predict what comes next and it's really about putting in a new situation trying to figure out what's a reasonable thing to do. Then we do a reinforcement learning step where it actually tries out ideas and it gets rewards and punishments based on how well it did. You know just positive signal, negative signal, not... you're not beating it. Exactly. Not at all. Yeah. Just just this signal. Um and then the hard part is well how do you judge? How do you decide if something was thumbs up or thumbs down. And so in math and science, much easier than in some of these more open-ended fields, but we also have AIs that are getting much smarter and much more able to provide that kind of reward signal. And so I think that the part of the challenge has been how do you expand the set of tasks that can be graded and that's been a lot of the focus. And uh there is actually very interesting... like a lot of this stuff dates back to the very beginning of OpenAI. We kind of had a picture this is how it would go. But I would just say I think we're getting there. I think we definitely have a lot more progress to make. Um, but yeah, hopefully you can keep giving us feedback and we'll be able to improve it for you.
One embedded challenge in that is that the writing you want is very different than the writing that most people want. And right now we have to, you know, make a model that about a billion people use and all kind of like. And what we'd like to do is to get the model so good at personalization that you think it's a great writer and some other person that has a very different kind of life and set of needs than you also thinks it's a great writer for what they want and those are very different things.
I think that's what I'm kind of asking though, like for the personal AGI, you would want it to have that sparkle, that soul, that sort of that magic, right? And I just... if it's not... and I saw, you know, obviously Yann LeCun's been arguing against this for a long time. I think I caught this Demis thing very quick where he seemed to be kind of aligned with you guys, but you know that LLMs will get us there, but he seemed to be saying we still need a couple more ticks maybe of something special to... but you guys seem so confident.
If the model can solve... we haven't tried to make it be, you know, what Ashley Vance will think is a great writer. We have tried to make it, you know, solve open math problems that the smartest mathematicians in the world can't solve. And I don't want to say anything about your intelligence relative to these mathematicians, but I think...
But I was going to say like, you know, solving math is also hard. So if we can do that, I'm pretty confident that this approach can also learn what you think is great writing and figure out how to do it for you.
By the way, we also have some new models coming on this dimension as well. So after this podcast comes out, I can't wait to judge it. Let us know. Let us know if it looks better.
Writing. I think personality and I think we're always improving like all the capabilities just moving up the jagged frontier. And so I think in this field it's always really important to judge not the current position but what has that slope been and also fit it to an exponential. And so if you think about how does the writing stack up compared to a year ago... sorry we disappointed with GPT-5. Uh don't worry we're very motivated to really deliver. Um, but I think that I think we really have a line of sight for how to improve it for every application that people want.
Since day one, the Core Memory podcast has been supported by the fine people at E1 Ventures. They are a young and ambitious VC firm in Silicon Valley investing in young and ambitious companies and people. Thank you so much to E1 Ventures for all your support. In the world that you guys have outlined, um this technology... okay you know say everything is working great and this is a quite optimistic scenario um diseases are being cured um resources are becoming more abundant problems are being solved so humanity as a whole is being lifted up. It's... I still don't see... I mean it seems like very... some of the world's smartest people are developing this technology it strikes me it will disproportionately benefit um in almost all scenarios even though like everyone might get lifted up a bit that um you know things really get more extreme because every time um what you guys are talking about about how you would manipulate these tools use these... I just feel like... I feel like things will go even more extreme and the joke of the permanent underclass and that sentiment of like seeing these really powerful tools and feeling like oh my gosh what am I even here for then? And feeling very disenfranchised.
Yeah. Like you can have all this time to do fun creative things.
I just feel like other people will be manipulating this in such extreme fantastic ways.
This is at the core of the OpenAI mission. Like this is really why we started this place because you see this powerful technology coming. It's going to be the most important technology ever created. How do you ensure it benefits everyone? Like truly all of humanity. Like that is in our mission. Ensure AGI benefits all of humanity. And we really mean it. And if you look at our corporate structure, we've tried multiple different iterations at trying to in the structure codify some of our values of how do we ensure that this is something that really does benefit people. You see it in the product choices we make, right? We decided to launch ChatGPT because we really believe this is technology that we need to be able to put into people's hands. And that was very controversial by the way that there was a different school of thought saying that the way to do it is you have to build it in secret that you can't give people access that you need to do in this other way and I think that when we look at the how do we actually make society resilient how do we actually benefit people it all kind of points to the direction that we have been going and there's a lot of nuance to it um but I think that the way that we're headed is very much that I think the floor for everyone is not going to go up just a bit like I think we are going to head to this world where I mean you think about even having a doctor in your pocket that's better than the best medical team that anyone in the world could get today accessible to anyone who has a smartphone like that is coming and that'll be free right that is a wild wild fact that's not a small... it's going to be a little bit better that is fundamentally raising the floor in this massive way now I think the question of also raising the ceiling I think that's fair too right I think that the question of exactly how the distribution goes and we think about this a lot you look at the OpenAI Foundation that has somewhere between 25% 30% somewhere around there of OpenAI equity right that's like more than 150 billion dollars if it is the case that OpenAI becomes very successful that all of that value locked up in the nonprofit like that is something that will be for really benefiting the world and we think that's...
Well we were at dinner the other day just real quick and I was listening to you talk about what you do with agents and I've known you I mean look you're fucking smart as fuck and I was just like Jesus man Greg with this machine. And I like even though I feel like I'm doing interesting things that help me out, when I heard you describing your life and what you were doing, I was just like, 'Oh my god, man. I mean, there's just going to be super people running around.' Um, I don't know. It was like kind of intimidating really. I mean, it was cool, but it was also quite intimidating. I'm like, 'I don't know how to use this like you do at all.'
Can I try a less sanitized version of...
Um, I hope I don't get in trouble for this. Uh, I can see three futures of the world. Um, I can see one where, as Greg was saying, the floor comes way up. You know, everybody gets subjectively like 10 times richer. Just the sort of material abundance, the prosperity is crazy huge. People are like, 'Man, relative to my life a decade ago, I'm doing great.' But also in that world these people who really learn how to use agents and get a lot of compute together and whatever we have some trillionaires you know maybe 10 trillionaires whatever. So like the floor comes way up like dramatically up but because this is a lever that people can really use uh the sort of like most capable most ambitious the people who already started rich and have access to a lot of compute inequality gets worse. So that's one world I can see. Um, I can see another world where we through many different kinds of things that could happen. Um, the floor doesn't come up as much. We don't generate as much total prosperity, but also there's like less inequality. So maybe people in a decade feel like twice as rich, but inequality has come down. Um, and actually I'll just like stop and talk to those two because I think this is like the real crux of the issue.
Was the third much scarier?
No, but it's like a distraction from the point I want to make. I think a lot of people in the world... like we think it's obvious, Greg, and I think it's obvious that people should prefer the first. I assume you also agree with that. Um, but emotionally, it's not where a lot of people are.
Well, I was going to say I don't want to claim what is obvious or not. But I think for me personally I just see so much potential in this technology and I think it's just so important from a societal level just thinking about even American competitiveness like you look at robotics like I don't think that we are ahead in robotics at all.
But we are not... with the software side we do have this opportunity and I think that is something all of these factors together in my mind are worth considering at once.
Yeah, I mean clearly I mean actually people who disagree a lot of other things I think do agree that America needs to be competitive on chips and robots and AI and everything else but there's going to be this huge question about how we organize society and the economy and do we push for maximum prosperity and accept the inequality that'll come with that or do we say like actually we're going to constrain it because we're going to be more focused on the relative nature and the fear that well if we don't do something yeah maybe the world will get more prosperous but the people who are really good at using this are going to have all this power and you know emotionally I think intellectually it kind of seems clear to me emotionally I...
I really get why it's not clear and I really get the fear that if we let inequality run here, the compounding nature of this tool is something that we don't yet understand. Now, the last thing I'll say on this is kind of no matter what, I think everyone should want much more compute, much more infrastructure, and the cheapest possible access to AI because otherwise I think you really exacerbate inequality if there's a limited amount of this and the price goes up because of supply and demand and only the rich people have it.
Yeah, I wanted to just build on that because I think that to some extent, and some of this also plays back to earlier just how Sam and I work together, how we think, right? Because I think that laying out those two options, I guess actually a really good point where it's like, well, are those the only two options, right? Is there something that we're not seeing in the space? And I think that the last thing Sam said to me is an unlock in terms of thinking about so AI is really opportunity. AI is opportunity for everyone if you have access, right? If you have compute. If you don't have compute, you can't, right? No matter how good you are with agents, if you don't have the compute to run them, you're not going to be able to do much. And so, I think a world where if everyone does have access to compute and, you know, I think for my generation growing up, we were much better at using computers than our parents, right? We grew up with it. We were, you know, native. And I think that the generation growing up now are going to be as good as I am at using agents, I think they're going to be 10 times better. It's wild to watch that.
It is crazy. I mean, I wrote this is like the first massive story on Core Memory was that dude who built the nuclear fuser with Claude. I just remember it was the fuser didn't even sort of matter as much as like what I saw him doing with his computer. I'm like, you just use this thing different, you know, he's like 22 and he has eight AI applications up and if you can get compute to that kid, if you can get compute to every kid, then it is really going to be the most extreme version of the American dream, right? Where it's really anyone who has the desire, the willpower to really play with this technology, to really lean in, to build with it, to get the most out of it. I think you're going to see this outperformance and I think you're going to see people have all sorts of mobility. And so I think that to some extent the right way of answering this question of option one versus option two is to say exactly something else. And I think it's possible.
I feel like we're doing some broad stuff and we have a bunch of specific questions. I'm gonna be bad and ask one more broad one. That's okay. Just based on what we were talking, I mean you guys probably know, maybe you don't. You know, I just cover hardware so deeply. And I think I'm pretty, I would venture to say I probably been to more factories and hardware startups in the US than just about anyone and keep an eye on China. I mean, the thing that always plays through my head is that yeah, we're ahead on software, we're ahead on AI. Software has been the story of the US for the last 40, 50 years of our strength. But you know when I think about how this technology manifests itself in the physical world I do not see a future where the US is competitive in any way shape or form not just in robotics but you know just all the componentry that goes in to these hardware systems. I go to El Segundo, I see 30 startups. It's great. There's like this flourishing of ideas and people trying things, but it's like such small potatoes compared to what I see in China. It just strikes me that there obviously will be a physical manifestation of all this in the world and the US just seems like extraordinarily disadvantaged to win that to me.
Well, I think of people who are working incredibly hard to try to change that. I'd say Sam is like on robotics in, well, I know through all the investments in different hardware companies or...
No, no, we're trying to figure out how robots are an obvious part of this and we're trying to figure out how to be very successful at robotics. I think if you could pick one thing to make the US competitive at manufacturing and the world of atoms in general, you would say we need a lot of robots that can build a lot more robots. But like we can't even make an actuator, like you know, like...
We're gonna figure that out. We will, OpenAI.
Okay. Like through your robotics.
We have to, we have to. But there's other parts of this that really matter. If you think about like the number of gigawatts of power that the world is going to need just to support AI workloads, the number of chips we're going to have to fabricate, the boring stuff about like how we're going to just get enough racks assembled and enough network cables strong and made in the first place. The US is extremely behind here. I think robotics will be the solution if you just look at how fast this has to happen and what the US is currently good at and how much infrastructure we have to build up and how long that would take to do by hand. But you are right in the diagnosis and the criticality of it. And I think luckily we have like a new piece on the chessboard.
Through OpenAI or the United States?
Tell me, I mean what do you mean?
I have a different feeling. I feel like we're play acting at hardware and we're gonna get completely hosed.
Well, on the code trajectory. Yes. No, we totally agree with that. If we can make true general purpose robots, if we can have a Codex equivalent power thing for robots that you can say like go configure a factory this way and make me more of this kind of robot or go figure out how to mine and refine this kind of thing, then the playing field changes.
Okay. But you said the US and not OpenAI specifically, but I feel like you're pointing at something that you know though.
