Greg Brockman on Astra and the Future of OpenAI

Navier-Stokes breakthrough

00:00We have Greg Brockman, the co-founder and president of OpenAI with us. Welcome to the show, Greg. How are you doing? >> Doing great. Thank you for having me. >> Thanks for hopping on. Uh huge day. Can we start with the with the math advances? What is what what is happening? Why is this important? Uh there's a lot of back and forth in the timeline, but I'd love for you to just set the table for us on what actually happened with uh Navier Stokes today. Well, uh it's always a huge day uh in uh AI and modern scientific progress, I would say. Yeah. Today we announced that our model had solved the Navier Stokes uh problem. Uh that we found a a counter example or a sort of proof that you can actually that these these uh theoretical

00:46equations do have a singularity or kind of break down under certain circumstances. And this is a problem that has been open for a very long time. It's one of the seven millennium problems which are kind of some of the deepest most important problems in mathematics and I I think that the problem itself is important right this is new knowledge for humanity that the proof itself is actually very elegant and beautiful and I think that there's a lot to learn from it and the the equations have lots of application and fluid dynamics in other areas but to me what's even more important is about what this represents about where we are in terms of model capabilities and the fact that we can actually generate new

01:22knowledge that we can learn from these models to and have them help us solve problems that are otherwise outside of reach or would take us a very long to solve. >> Yeah. I mean, where should I actually go with this? Is this going to help me book a flight? Is this going to help me cure cancer? Is this just going to help you recruit researchers who are fascinated by this stuff? Uh because I think that there's this is, you know, taken over the technology world. Uh but I imagine that this will not be something that gets talked about at backyard barbecues with friends and family that are three clicks removed from outside of >> Yeah. Yeah. >> Well, look, I think that there's first of all the applications of this specific

02:00result or the equations themselves, right, which are things that let us better understand phenomena from ocean currents to air flow around aircraft. Sure. Uh around, you know, turbulence and things like that. But it's really about the broader insights and methods that can help scientists and mathematicians further accelerate their research. And I think that again representative of if we have models that can help solve this kind of problem then what happens from here like what other problems that are immediately applicable. And I think that talking about curing diseases and new medicines we're going to be able to develop, all of that starts to become much more real when you have models that are at this

Why the math result matters

02:37level of assistance and capability. And I do think that there are going to be real changes to to think about in terms of we can have so much more ambition with the kinds of of challenges that we can hope to tackle now. >> Yeah. I I mean I think uh even even if this doesn't break through to the broader uh the broader world uh the weekend definitely will because it seemed like everyone was talking about Blender, talking about Astra building stuff. Uh take us through the launch of Astra, what the feedback has been, what you've learned. It seemed like there were a couple resets, the model scaled very well. Uh how was this launch different than previous launches? Well, first of all, I've just been blown

Astra launch and community reaction

03:21away by the community reaction to Astra. It's been really amazing and very humbling, honestly, to see all the creativity and the different ways that people have been applying the model. And I think that it's very clear that we've reached a new threshold of computer use. So, this model is able to really work with different kinds of applications in a way that was not previously possible. And people are taking full advantage of that fact and really thinking about how to create. I lots of people showing off 3D creations and >> mapping out physical locations and turning them into into these 3D models and thinking about can you use this for >> design of physical parts. Someone talked about how they were designing some

04:02mechanic for catching hair in a shower drain and that they were able to >> super cool, right? That that they're now able to actually manufacture that >> shower hair super intelligence. [laughter] Yeah. No, that stuff's so mundane, but it's so important. I I feel like uh a lot of this stuff gets lost. Right. >> Ex. Exactly. And I think there's a core there that's very important, which is that we are talking about these grand challenges sometimes or very esoteric applications, but really the everyday the number of problems that you have in your life that you would love to solve. It's now possible, right? That that we're really trying to empower the individual to make it so that you can be you can have superpowers, you can

04:39accomplish more. And I think that that you know, really trying to benefit people, empower people, build tools that can really help you and help you in your your daily life. That's all part of what we're we're we're working on. >> So, yeah, I mean, it seems like a huge number of people in uh in tech uh effectively rebuilt their entire house in Blender and planned a remodel this weekend. Uh thanks to Astra and but I am wondering about the merge and how you bring together codecs, chatt work, chacht on desktop. I have a gaming PC now with a Nvidia card in it. I have a Mac Mini. Like I have all these things and I can imagine that I'm just I'm doing that unnecessary or like it's fun for me, but uh that early adopter work

Unifying chat and agentic modes

05:23of going and unhobling it a little bit here and there, but in the future this will all just be tucked in one, you know, prompt box and it might build a 3D Blender model for to answer my question of should I remodel my house or not. Um, but how do you see the capabilities that we saw on display from sort of light power users over the weekend actually making their way into uh consumers who might not even know what Blender is. >> Well, I think you're exactly right that we really want to shift these tools from requiring kind of low-level sort of >> access or guidance to really having the human be able to fly, right? to really be empowered for you to be able to set the goals and the objectives and that

06:09you still should feel like you can get into those details and you can understand them. you can provide that oversight because ultimately you should feel accountable for the outcomes but you have this this absolute amplifier right like a trampoline or like a you know rocket ship for the mind like however you want to to to analogize it and I think what that means at a practical level so first of all this year we've been really seeing this shift from just pure chat use cases to gentic use cases but I would also keep in mind that chat is alive and well I mean we're we're now well over a billion users every week that you can see that the market share of chatbt is starting to climb once again because we've been

06:44investing so hard in in so many use cases that are important for people in education and health and a variety of other areas and then at the same time these productivity deep knowledge work use cases those are really taking off we've had this like almost vertical wall of agentic adoption since we launched chat GBT work and I think that the fact that these are two distinct modes that that is actually a point in time that is something that we're continuing to unify and merge and that we're starting to see that there's a new emerging form factor for how people want to consume AI. And I think that it's almost like that the promise of AI has always been that you have something that you can talk to and

07:21really delegate work to that's proactive and persistent. And that I what we were promised if you were to rewind five 10 years ago was never a low-level language model. You have to think about context windows and you have to select thinking strength and you have to select different models. Like none of that none of that is is the future. And so I think that we're moving towards real amplification, real giving you time back, real having computers that are able to operate according to your goals, to your desires. And I think that that is a core of it. We're developing this safely. That's that's one of the core commitments that that we make and how we think about this. Um but but we really see the power of these tools starting to

08:02really um really start to increase in terms of what people are capable of and that under the hood utilizing tools like blender so that that is almost a detail that fades into the background is absolutely the direction of travel. It feels like in AI particularly there's been a almost like a first mover disadvantage in that billions of people have tried Chad GBT and and some percentage of them tried it for the first time and have a certain impression of the product and what it can do and then you know even in the last few weeks there's been new agents and and products that come online and people try it and their mind is just completely blown and I think it's funny because I'm like well as somebody who's like you know trying

08:41to get the absolute max out of ChatG GBT. I'm like, well, I've been running like, you know, I've had like an agent running that, for example, will tell me every time a SpaceX launch is going to happen and if it gets delayed, right? These sort of like persistent agents that are running in the background. Um and but but strategically I feel like it's a it's a new kind of challenge because you have this the as capability has been been scaling first movers need to be almost like constantly reminding the the market of um all these just like new ways to use >> overhang. Yeah, we we think about this a lot and I think that there's this discovery problem that we as a field need to really encounter in a first

Discovery problem and marketing

09:22class way and we haven't done it fully yet, but I think we have a real shot at solving it better than any product before because >> the the thing that that right now we kind of rely on. You think about chat GBT chat GBT work. These are both text boxes, right? And it's like, well, this new text box is way more powerful than the old text box. And but oh, oh, there are some reasons that you still want to use the old text box. It's [laughter] not, you know, it's like far too confusing. People just want something that can help them solve their problem. The whole point is to get your time back, not for you to have to go and become an expert in all these these internal details. But at the same time,

09:55we also have a model that understands what you're trying to accomplish, right? That you're explaining to it, here's what I want. It has a lot of context on you. And so it should also be able to proactively say to you, hey actually if you ask me this other way or if you add added this connector or if you authorize me to do this or if you you know hook up your credentials in this in this way I can go and do this other thing for you and so we're thinking a lot about that self-nowledge that onboarding process and I think that is a huge huge opportunity and I think that there is both the the disadvantage that you cite of people tried it they form an impression and it's changed that it's something new but there's also an

10:32advantage I chat chatbt like over a billion users every week like that is unique no one has that kind of use on on these on these models and I think that the number of people who have tried chatbt before I think it's it's another you know billion billion and a half something like that and so that's a huge opportunity as well for us to go back to those users and say hey we can now solve the problem for you we can now help you in ways that you didn't see before and I think that it's it's true it's real you look at how many people use chat for health 300 million people every single week with health queries, right? And that that's really making a difference in people's lives and that of their loved ones. And so we have such

11:08opportunity. >> Can you stay there with with health and and and explain where >> one note before that? Something that I think is really interesting and I think something that OpenAI can can do a lot better is like when people talk about like everyone in AI wants to be like the Apple of AI from a marketing standpoint. When they when you think like Apple marketing, you're thinking like Mac versus PC or you're thinking 1984, these big branding campaigns. But the actual thing that Apple does really really well with marketing is they just hammer really really specific details about their products, right? They're like >> they're advertising the new camera. They're advertising Mimoji, right? They're advertising like

11:46>> certain features in Safari, right? And so it's like with AI, the surface area of like things that you need to communicate is actually like an order of magnitude greater because it can do so many different things. And so I think there's such an opportunity >> um for the company to focus advertising. The brand campaigns are awesome and like the the launch video for Astro was amazing, but it's like there should be billboards running of like very specific things that Chach BT can do to give you back your time. Um >> yes, this this has actually been a real sort of realization or just like something that I have really come to over the course of of of this year. And if you look at even for example the you

12:23know we just announced chat GBT images 2.5 >> and if you look at the launch video there the thing that I love about it is it shows here's someone creating an image and here's like a bunch of different variations of it and then here's them taking their favorite one and having it in the world. like someone said, "Here's a cool like little sketch of a candle holder." You see an awesome visualization of it and then you see the physical candle holder and you're just like that's what you want, right? It's like you it speaks to you immediately. And I think that that really showing people here's a use case. And the thing that was also a little surprising to me is that we've sometimes highlighted esoteric use cases, something that

12:59appeals to someone in particular and it's amazing for that person, but people don't then say, "Oh, because it's this powerful, I can also do this other powerful thing I've been waiting on." like that connection is is is is something that is less sort of easy to make than I than I'd realize and it makes sense. What you want is to for there to be use cases where people say I actually want that particular thing now let me go try it myself and then from there you start exploring and you start to find I [clears throat] actually do have this powerful use case that I didn't even realize was tip at the time. >> Yeah. Studio is probably like the best example of that working really really well. >> The other thing is is reminding people

13:33to ask the AI what it's capable of. Yeah, like I was I was having lunch with a buddy who's a real estate developer and he is using chat all day long for different like deal memos and to understand like projects that he's working on all this stuff and he'll ask me he'll ask me all the time can can catch GPT do this or that and I'm like I'm happy to I'm happy to answer you but like you have the thing that will just explain exactly how to do the thing that you want to do or or maybe not but it probably can. >> Yeah, I I I did the same thing. I was kicking off this Blender thing and I was like, should I run this as a local codeex thread or in the cloud? Let me know which one's better based on my system and it gave me a good answer and

14:11I was able to go for it. >> On on images, uh when when images 2 came out, I had some moments where I thought, okay, images is solved. Like where do you where do you think images actually go as a category? because it felt uh like this has been something that has maybe oneshoted me more than anything else. specifically with like when it when it released, I was I was um >> uh spending hours like like on a Saturday trying to design furniture, right? And just going through like you know hundreds and hundreds of prompts. But how how far can image models go and where are they going and what are the ways in which you think they can um they can be applied? We were talking earlier too about the downstream impact of of

Image models and quality thresholds

14:53image models. If you can take, you know, a a physical space somewhere and take a picture of it and imagine it as all these other variations, there's so much like real world activity that will be driven from that because people can see this thing. >> Yeah. >> Visually and say like I now I want to go make that reality which I think is really cool. >> Well, I think that's exactly the right way to think about it is as you hit new thresholds of capability, my experience has always been that fundamentally new applications become unlocked in ways that you almost wouldn't have thought about ahead of time. And so I think that within for example knowledge work, professional work, marketing, all those areas, you just need to be above a

15:31quality threshold. If you're below it, it's a cool concept, but you can't actually use the final material, right? That that then means that you you haven't really solved the problem. and that having precise edit control, being fast and really being creative and having a diversity of different results and also being able to >> have this this good interplay back and forth with a person. I think that that really unlocks whole new use cases and I think there's a huge market there and even for example the kinds of things you may not think of naively but actually start to be really important applications we're seeing happening is slide creation or making awesome websites, right? Being able to have that

16:08image generation capability in the middle is something that's very unique to OpenAI uh relative to to some of our competitors. And I think that you're able to then produce much better artifacts downstream. And so we really view images, we view voice, we view coding, all of these capabilities as one package that are going to come together to create an AI that empowers you. That means you can create anything that you imagine. And I think it's going to be something that's just unlike anything out there. Let's go back to health. I think most people already are aware that you can synthesize some lab data with some sleep scores, but your vision that you laid out recently for where that product goes is much more complex, much

ChatGPT Health's three pillars

16:51deeper. So, uh tell me where uh ChatBT Health is going in the future. >> Well, I would think of it as there are three sides to what we do on health. There's the consumer side again 300 million people every week with health queries. >> There's the clinician side which is bottoms up >> and that's really about think of it a chatbt that's really tuned for clinicians that gives them direct citations to medical literature things like that. >> There's a third pillar which is the enterprise side of selling directly to hospitals and them enabling it. And you can see things like we have an integration within Epic and really trying to bring each of these three pillars the best possible service independently. But you think about as

17:36those really build momentum that you actually are able to get synergies across them, right? That there's something that actually makes the health experience and the ability to really transform health care in America and the world on the table because there's so many think about how much work you as a patient have to do. If you're talking to different specialists, you have to carry your medical record from one to the other. You have to explain again here's the issue and that ultimately you're on the hook. You're the doctor who has to make the decision whether you like it or not. And actually being able to have just good sharing of of that information across different providers that becomes possible if everyone's on one platform

18:08or think about clinical trial enrollment. That's a huge bottleneck to drug development and finding people who are eligible and will benefit from being involved in a particular trial. And if you have that kind of of data, if people are willing to sort of, you know, entrust you with that information, that that's something can actually really benefit them and benefit the world at the same time. And so what I view us as building is really trying to build the world's best healthcare platform to really be able to bring health care into the AI age. And I think that it's something that is going to be absolutely transformative to many people's quality of life, really uplift so many people, and we're seeing it already in such

18:44concrete ways. Some of my favorite stories about chatbt are people who say, "Hey, information I got from chat helped me save my own life. Help me save that of a loved one that there was this medical issue that someone had and that I if you know the doctor told me one thing, I was able to to double check that and understand what they were saying and be able to to push back on it and got to a good outcome." And that happens every single day. So I think that health with these AIs is something that it we're still just scratching the surface of what's possible and I think it's one of the most positive applications of AI that that you can you can think of. Yeah, I'm very interested to see how uh the advancements in memory

19:20intersect with health because I expect that uh chatbt with where memory has gone where I'll be in a new thread and it will bring up just the right information or tie back to a thread that maybe happened three weeks ago. When you actually apply that to like health related queries, it may be able to like pick up patterns that sometimes would take a human years to figure out like a certain ailment or something like that where it's like, hey, you're asking about all these different things and maybe you thought they were not connected. Turns out they they actually are and you should go down this sort of like rabbit hole. >> Last question. I'm sorry. Please. >> I was I was going to say I think that's

19:59absolutely right. We're seeing that very concretely and we've seen you know just in my own personal life my my wife you know talked about some of her her medical conditions publicly but I it was really this five-year journey of talking to many specialists each one who was kind of touching one part of the elephant and would try to address that one part and it was only finally her allergist who said hey I think all these symptoms you're seeing are connected and you have this uh genetic condition that affects all of your subsystems and that's the kind of thing where it's really hard to say how many people have similar kinds of conditions and just never find out. How many people have these areas where it's like if you just

20:35sort of are functionally specialized that you're never going to bring together the whole diagnosis and I think that is one of the powers and potentials of an AI that really deeply is able to help you across all parts of your life and also is a deep domain expert in all areas of medicine. >> Yeah. Uh I have one last question. Uh what how do you tell the story of operator? It feels like it was a failure or a side quest, but it feels incredibly important now given the advances in computer use. Is there a clear lineage there? What was operator? Does that still exist somewhere within chat GPT? H how does how did how did computer use get solved? >> Yeah. Well, look, I would look at all these things as timing and all about

Operator to Astra lineage

21:20iterative deployment. Yeah. Right. that that there's a moment where you need to where the capabilities aren't quite there but actually learning from real world deployment is very helpful right and the I think operator was just kind of below threshold in terms of the model capabilities it was a cloud-based system that operated with computer use but it was slow it wasn't fully accurate it was like pretty painful to to use some people got value but it really wasn't above threshold and if you look at what's happened that the team like one thing openai does very well is we make long-term investments on things that really matter and we do the grind and that the team this year I think really started to build momentum that we put in

21:59a lot of effort to go and sort of burn down a long list of issues were able to really focus on solving computer use and I think that they delivered in a significant way and there's more to do never done all those things but it's a true milestone I think people are really appreciating what's possible because we've been in a world with these agents using computers through connectors right through these very painstakingly coded systems that are so different from how humans use computers. Whereas humans can already use everything on a computer, right? Everything's designed for people. So if you have an AI that can operate that way and even from the very beginning of OpenAI, we had a dream that one day we could create such an AI, it

22:37becomes able to help you across everything that you would be able to do with a computer yourself. And so I think we're there with Astra. I think that there's just so much more that people are going to uncover in terms of applications where this can go. But it's an example of long-term focus, doing the work, and not giving up even when the going gets tough. >> Yeah. And it feels like Astra, my view is it really felt like all these different bets coming together, you know, at the right at the right time, right? The the advancements in in the model itself, the the computer use, voice, all these things. Um, and it uh it's all it's all making sense. So, >> yeah. >> Um, >> together, it's focus. It's uh it's

23:15something that I think this company does extremely well when we really put a challenge in front of us and think about how to accomplish it safely well and uh to to really deliver the value we're doing thing. >> Yeah. put different differently, it felt like when you look at last year, it felt like OpenAI was uh operating like a big company and it and it was a big company but but the way in which like product experimentation was happening was you know when you think of like a hyperscaler they'll launch a new product thinking okay if there's a 20% hit rate or even a 10% or 5% chance that's okay and then this year it feels like actually the entire company switched back into actual startup mode which is

Startup focus and closing

23:54like you know focus focus focus all these things need to come together the whole team needs to be rowing in the same direction and then the difference in momentum and growth and all these things uh coming from that and and uh actually taking the company from like operating and shipping more like a big company to shipping again and focusing like a startup has been uh feels like an impossible task and it's been uh incredible to watch. So >> yeah, >> thank you. No, it's been a real real effort from many many people at OpenAI to really bring together and something that that I really value that I think we really value as a company and I think that we're just so laser focused on our mission and really thinking about every

24:32piece of what we do should add up to helping us accomplish it. >> Well, thank you so much for taking the time to come chat with us. >> Great to see you. >> We'll talk to you soon, Greg. >> Thank you. >> Talk the rest of your day. Goodbye.