Sam Altman: How OpenAI Wins, AI Buildout Logic, IPO in 2026?

0:00You know, that$1.4 trillion you mentioned, we'll spend it over a very long period of time. I wish we could do it faster. I think it would be great to just lay it out for everyone once and for all how those numbers are going to work. Exponential growth is usually very hard for people. OpenAI CEO Sam Altman joins us to talk about OpenAI's plan to win as the AI race tightens, how the infrastructure math makes sense, and when an OpenAI IPO might be coming. And Sam is with us here in studio today. Sam, welcome to the show. Thanks for having me. So OpenAI is 10 years old. It's crazy to me. ChatGPT is three, but the competition is intensifying.

0:36This place where OpenAI headquarters was in a code red, is in a code red after Gemini 3 came out. And everywhere you look, there are companies that are trying to take a little bit of OpenAI's advantage. And for the first time I can remember, it doesn't seem like this company has a clear lead. So I'm curious to hear your perspective on how open ai will emerge from this moment and when first of all on the code red point we view those as like relatively low stakes somewhat frequent things to do i think that it's good to be paranoid and act quickly when a potential competitive threat emerges this happened to us in the past that happened earlier this year with deep seek um and there was a code red back then too yeah there there's there's a saying about pandemics which is something like when a pandemic starts, every bit of action you take at the beginning is worth much more than action you take later.

1:33And most people don't do enough early on and then panic later. And you certainly saw that during the COVID pandemic. But I sort of think of that philosophy as how we respond to competitive threats. And, you know, I think it's good to be a little paranoid. Gemini 3 has not, or at least has not so far, had the impact we were worried it might. But it did, in the same way that deep seek did identify some weaknesses in our product offering strategy and we're addressing those very quickly i don't think we'll be in this code red that much longer uh you know like these are not these are historically these have been kind of like six or eight week things for us um but i'm glad we're doing it uh just today we launched a new image model which is a great thing and that's something consumers really wanted last week we launched 5.2 which is going over extremely well and going very quickly we'll have a few other things to launch and then we'll also have some continuous improvements like speeding up the service but you know i think this is like my guess is we'll be doing these once maybe twice a year for a long time and that's a part of really just making sure that we win in our space um a lot of other companies will do great too and i'm happy for them but you know chat gbt is still uh by far by far the dominant uh chatbot in the market and i expect that lead to increase not decrease over time um the the models will get good everywhere but a lot of the reasons that people use a product consumer or enterprise uh have much more to do than just with the model and we've you know been expecting this for a while so we try to build the whole cohesive set of things that it takes to make sure that we are, you know, the product that people most want to use.

3:21I think competition is good. It pushes us to be better. But I think we'll do great in chat. I think we'll do great in enterprise and in the future years, other new categories, I expect we'll do great there too. I think people really want to use one AI platform. People use their phone at their personal life and they want to use the same kind of phone at work most of the time. We're seeing the same thing with AI. The strength of ChatGPT consumer is really helping us win the enterprise. Of course, enterprises need different offerings, but people think about, okay, I know this company opening up and I know how to use this ChatGPT interface.

3:55So the strategy is make the best models, build the best product around it and have enough infrastructure to serve it at scale. Yeah, there is an incumbent advantage. ChatGPT, I think earlier this year was around 400 million weekly active users. Now it's at 800 million, reports say approaching 900 million. But then on the other side, you have distribution advantages at places like Google. And so I'm curious to hear your perspective. Do you think the models are going to commoditize? And if they do, what matters most? Is it distribution? Is it how well you build your applications? Is it something else that I'm not thinking of?

4:33I don't think commoditization is quite the right framework to think about the models. there will be areas where different models excel at different things for the kind of normal use cases of chatting with a model maybe there will be a lot of great options for scientific discovery you will want the thing that's right at the edge that is optimized for science perhaps so models will have different strengths and the most economic value i think will be created by models at the frontier and we plan to be ahead there um and we're like very proud that 5.2 is the best reasoning model in the world and the one that scientists are having the most progress with.

5:12But also, we're very proud that it's what enterprises are saying is the best at all the tasks that a business needs to do its work. So there will be times that we're ahead in some areas and behind in others, but the overall most intelligent model, I expect to have significant value, even in a world where free models can do a lot of the stuff that people need. The products will really matter. Distribution and brand, as you said, will really matter. In ChachiPT, for example, personalization is extremely sticky. People love the fact that the model gets to know them over time, and you'll see us push on that much, much more.

5:52People have experiences with these models that they then really kind of associate with it. And I remember someone telling me once like you kind of pick a toothpaste once in your life and buy it forever or most people do that apparently um and people talk about it they have one magical experience with chat gpt health care is like a famous example where people put their um you know they put a blood test into chat gpt or put their symptoms in and they figure out they have something and they go to a doctor and they get cured of something they couldn't figure out before like those users are very sticky uh to say nothing of the personalization on on top of it um there will be all the product stuff uh we just launched our browser uh recently and i think that's pointing at a new uh you know pretty good potential moat for us uh the devices are further off but i'm very excited to to do that so i think there'll be all these pieces and then the enterprise uh what creates the moat or the competitive advantage.

6:57I expect it to be a little bit different, but in the same way that personalization to a user is very important in consumer, there will be a similar concept of personalization to an enterprise where a company will have a relationship with a company like ours and they will connect their data to that. And you'll be able to use a bunch of agents from different companies running that. And it'll kind of like make sure that information is handled the right way and i expect that'll be pretty sticky too um we already have more than uh a million people think of us largely as a consumer company yeah we are going to definitely get into enterprise yeah yeah you know like share the stat why didn't actually a million we have more than a million enterprise users but we have like just absolutely rapid adoption of the api um and like the api business grew faster for us this year than even ChatGPT.

7:48Really? So the enterprise stuff is also, you know, it's really happening starting this year. Can I just go back to this? Maybe if commoditization is not the right word, model some maybe parity for everyday users. Because you started off your answer saying, okay, maybe everyday use will feel the same, but at the frontier, it's going to feel really different. When it comes to ChatGPT's ability to grow, So if I'll just use Google as an example, if ChatGPT and Gemini are built on a model that feels similar for everyday uses, how big of a threat is the fact that, you know, Google has all these surfaces through which it can push out Gemini, whereas ChatGPT is fighting for every new user?

8:34I think Google is still a huge threat, you know, extremely powerful company. if google had really decided to take us seriously in 2023 let's say we would have been in a really bad place i think they would have just been able to smash us um but their ai effort at the time was kind of going in not quite the right direction product wise they didn't you know they had their own code red at one point but they didn't take it that seriously everyone's doing wild reds out here um and then and also google has probably the greatest business model in the whole tech industry um and i think they will be slow to give that up um but bolting ai into web search i don't maybe wrong maybe like drinking the kool-aid here i don't think that'll work as well as reimagining the whole this is actually a broader trend i think is interesting bolting ai onto the existing way of doing things i don't think is going to work well as redesigning stuff in this sort of like ai first world that's part of why we wanted to do the consumer devices in the first place but it applies at many other levels um if you stick ai into a messaging app that's doing a nice job summarizing your messages and drafting responses for you that is definitely a little better but i don't think that's the end state that is not the idea if you have this like really smart ai that is like acting as your agent talking to everybody else's agent and figuring out when to bother you and not to bother you and how to you know what decisions it can handle and when it needs to ask you.

10:04So similar things for search, similar things for like productivity suites. I suspect it always takes longer than you think, but I suspect we will see new products in the major categories that are just totally built around AI rather than bolting AI in. And I think this is a weakness of Google's, even though they have this huge distribution advantage. Yeah. I've spoken with so many people about this question. When ChatGPT came out initially, I think it was Bendig Devins that suggested you might not want to put AI in Excel. You might want to just reimagine how you use Excel. And to me, in my mind, that was like you upload your numbers and then you talk to your numbers.

10:42But one of the things people have found as they've developed this stuff is there needs to be some sort of back end there. So is it that you sort of build the back end and then you interact with it, with AI, as if it's a new software program? Yeah, that's kind of what's happening. Why wouldn't you then be able to just bolt it on on top? I mean, you can bolt it on on top, but the. I spend a lot of my day in various messaging apps. Including email, including text, Slack, whatever. I think that's just the wrong interface. So you can bolt AI on top of those. And again, it's like a little bit better.

11:18But what I would rather do is just sort of like have the ability to say in the morning, here are the things I want to get done today. Here's what I'm worried about. here's what i'm thinking about here's what i'd like to happen i do not want to be i do not want to spend all day messaging people i do not want you to summarize them i do not want you to show me a bunch of drafts deal with everything you can you know me you know these people you know what i want to get done um and then you know like batch every couple of hours updates to me if you need something but that's a very different flow than the way these apps work right now yeah and i was going to ask you what ChatGPT is going to look like in the next year and then the next two years.

11:59Is that kind of where it's going? To be perfectly honest, I expected by this point ChatGPT would have looked more different than it did at launch. What did you anticipate? I don't know. I just thought like that chat interface was not going to go as far as it turned out to go. Like we, I mean, it was put up. It looks better now, but it is broadly similar to when it was put up as like a research preview. It was not even meant to be a product. We knew that the text interface was very good, you know, like everyone's used to texting their friends and they like it. The chat interface was very good, but I would have thought to be as big and as significantly used for real work of a product as what we have now, the interface would have had to go much further than it has now i still think it should do that but there is something about the generality of the current interface that i underestimated the power of um what i think should happen of course is that um ai should be able to generate different kinds of interfaces for different kinds of tasks so if you are talking about your numbers it should be able to show you that in different ways and you should be able to interact with it in different ways um it and we have a little bit of this with features like canvas it should be way more interactive it's like right now you know it's kind of a back and forth conversation it'd be nice if you could just be talking about an object and it could be continuously updating you have more questions more thoughts more information comes in um it'd be nice to be more proactive over time where it maybe does understand what you want to get done that day and it's continuously working for you in the background and send you updates and you see part of this the way people are using codecs which i think is one of the most exciting things that happened this year is codex got really good uh and that points to a lot of what i hope the shape of the future looks like um but it is surprising to me i was gonna say embarrassing but it's not i mean clearly it's been super successful uh it is surprising me how little chat gpt has changed over the last years.

14:14Yeah. The interface works. Yeah. But I guess what the guts have changed. And you talked a little bit about how personalization is big to me. And I think this has been one of your preferred features to memory has been a real difference maker. I've been having a conversation with ChatGPT about a forthcoming trip that has lots of planning elements for weeks now. And I can just come in in a new window and be like, all right, let's pick up on this trip. And it has the context and it knows the guide I'm going with. It knows what I'm doing. The fact that I've been like planning fitness for it and can really synthesize all of those things.

14:52How good can memory get? I think we have no conception because the human limit, like even if you have the world's best personal assistant they don't they can't remember every word you've ever said in your life they can't have read every email they can't have read every document you've ever written they can't be you know looking at all your work every day and remembering every little detail they can't be a participant in your life to that degree and no human has like infinite perfect memory um and ai is definitely gonna be able to do that and we actually talk a lot about this like right now memory is still very crude very early we're in like the you know the gpt2 era of memory but what it's gonna be like when it really does remember every detail of your entire life and personalized across all of that and not just the facts but like the little small preferences that you had that you maybe like didn't even think to indicate but the ai can pick up on uh i think that's going to be super powerful.

15:56That's one of the features that still maybe not a 2026 thing, but that's one of the parts of this I'm most excited for. Yeah, I was speaking with a neuroscientist on the show and he mentioned that you can't find thoughts in the brain. The brain doesn't have a place to store thoughts, but computing, there's a place to store them so you can keep all of them. And as these bots do keep our thoughts, of course, there's a privacy concern. But the other thing is something that's going to be interesting is we'll really build relationships with them. I think it's been one of the more underrated things about this entire moment is that people have felt that these bots are their companions, are looking out for them.

16:38And I'm curious to hear your perspective. When you think about the level of, I don't know if intimacy is the right word, but companionship people have with these bots, is there a dial that you can turn to be like oh let's make sure people have become really close with these things or you know we turn the dial a little bit further and there's an arms distance between them and and if there is that dial how do you modulate that the right way there are definitely more people than i realize that want to have let's call it close companionship i don't know what the right word is like relationship doesn't feel quite right companionship doesn't feel quite right i don't know what to call it but they want to have whatever this deep connection with an ai is there there are more people that want that at the current level of model capability than i thought and there's like a whole bunch of reasons why i think we underestimated this but at the beginning of this year it was considered a very strange thing to say you wanted that maybe some a lot of people still don't revealed preference you know people like their ai chatbot to get to know them and be warm to them and be supportive and there's value there even for people who in some cases even for people who say they don't care about that uh still have a preference for it i i think there's some version of this which can be super healthy and i think you know adult users should get a lot of choice in where on the spectrum they want to be there are definitely versions of it that seem to me unhealthy although i'm sure a lot of people will choose to do that um and there's some people who definitely want the driest most effective efficient tool uh possible so i suspect like lots of other technologies we will run the experiment we will find that there's unknown unknowns good and bad about it and society will over time figure out how to think about where people should set that dial and then people have huge choice and set it in very different places.

18:45So your thought is allow people basically to determine this. Yes, definitely. But I don't think we know how far it's supposed to go, how far we should allow it to go. We're going to give people quite a bit of personal freedom here. there are examples of things that we've talked about that you know other services will offer but we won't like we're not going to let we're not going to have RAI you know try to convince people that should be like an exclusive romantic relationship with them for example gotta keep it open no I'm sure that that will happen with other services because the stickier it is the more money that service makes all these possibilities kind of They're a little bit scary when you think about them a little bit deeply.

19:33Totally. This is one that really does, that I personally, you can see the ways that this goes really wrong. Yeah. You mentioned enterprise. Let's talk about enterprise. You were at a lunch with some editors and CEOs of some news companies in New York last week and told them that enterprise is going to be a major priority for OpenAI next year. I'd love to hear a little bit more about why that's a priority, how you think you stack up against Anthropic. I know people will say this is a pivot for OpenAI that has been consumer focused. So just give us an overview about the enterprise plan. So our strategy was always consumer first.

20:12There were a few reasons for that. One, the models were not robust and skilled enough for most enterprise uses. And now they're getting there. the second was we had this like clear opportunity to win in consumer and those are rare and hard to come by and i think if you win in consumer it makes it massively easier to win in enterprise and we are we are seeing that now but as i mentioned earlier this was a year where we enterprise growth outpaced consumer growth and given where the models are today where they will get to next year. We think this is the time where we can build a really significant enterprise business quite rapidly.

20:55I mean, I think we already have one, but it can grow much more. Companies seem ready for it. The technology seems ready for it. Coding is the biggest example so far, but there are others that are now growing, other verticals that are now growing very quickly. and we're starting to hear enterprises say, you know, I really just want an AI platform. Which vertical company? Finance. Science is the one I'm most excited about of everything happening right now, personally. Customer support is doing great.

21:32But yeah, we have this thing called GDP, though. I was going to ask you about that. Can I actually throw my question out? Sure about that. All right, because I wrote to Aaron Levy, the CEO of Box. And I said, I'm going to meet with Sam. What should I ask him? He goes, throw a question out about GDP value, right? So this is the measure of how AI performs in knowledge work tasks. And I said, okay, I went back to the release of GPT 5.2, the model that you recently released and looked at the GDP value chart. Now this, of course, it's an open AI evaluation. That being said, the GPT 5 thinking model.

22:06So this is the model released in the summer. it tied knowledge workers at 38 % of tasks. Beat or tied, I think. Beat or tied. So 38.8%. GPT 5.2 thinking beat or tied at 70.9 % of knowledge work tasks. And GPT 5.2 pro, 74.1 % of knowledge work tasks. And it passed a threshold of being expert level. It handled, it looks like something like 60 % of expert tasks, of tasks that would make it, you know, on par with an expert in the knowledge work. What are the implications of the fact that these models can do that much knowledge work? So, you know, you were asking about verticals and I think that's a great question.

22:52But the thing that was going through my mind and why I kind of was stumbling a little bit is that eval, I think it's like 40 something different verticals that a business has to do. there's make a PowerPoint do this legal analysis you know write up this little web app all this stuff and and the eval is do experts prefer the output of the model relative to other experts for a lot of the things that a business has to do now these are small well-scoped tasks these don't get the kind of complicated open-ended creative work that you know figure out a new product these don't get a lot of collaborative team things but a co-worker that you can assign an hour's worth of tasks to and get something you like better back 74 or 70 of time if you want to pay less is still pretty extraordinary if you went back to the launch of chat tbt three years ago and said we were going to have that in three years most people say absolutely not um and so as we think about how enterprises are going to integrate this, it's no longer like just that it can do code.

23:56It's all of these knowledge work tasks you can kind of farm out to the AI. And that's going to take a while to really kind of figure out how enterprises integrate with it, but should be quite substantial. I know you're not an economist, so I'm not going to ask you, what is the macro impact on jobs? But let me just read you one line that I heard. in terms of how this impacts jobs from Blood in the Machine on Substack. This is from a technical copywriter. They said, chatbots came in and made it so my job was managing the bots instead of a team of reps. Okay, that to me seems like it's going to happen often.

24:36But then this person continued and said, once the bots were sufficiently trained up to offer good enough support, then I was out. Is that going to become more common? Is that what bad companies are going to do? Because if you have a human who's going to be able to sort of orchestrate a bunch of different bots, then you might want to keep them. I don't know. How do you think about this? So I agree with you that it's clear to see how everyone's going to be managing like a lot of AIs doing different stuff.

25:08Eventually, like any good manager, hopefully your team gets better and better. But you just take on more scope and more responsibility. I am not a jobs doomer. Short term, I have some worry. I think the transition is likely to be rough in some cases. But we are so deeply wired to care about other people, what other people do. we are so we seem to be so focused on relative status and always wanting more and to be of use and service to express creative spirit whatever whatever whatever has driven us this long i don't think that's going away now i do think the jobs of the future or i don't even know if jobs is the right word whatever we're all going to do all day in 2050 probably looks very different than it does today um but i but i i don't have any of this like oh life is going to be without meaning and the economy is going to totally break like we will find i hope much more meaning and the economy i think will significantly change but i think you just don't bet against evolutionary biology um you know i think a lot about how we can automate all the functions at open ai and then even more than that i think about like what it means to have an ai ceo open ai it doesn't bother me i'm like thrilled for it i won't fight it uh like i don't want to be i don't want to be the person hanging on being like i can do this better the handmade way ai ceo just make a bunch of decisions to sort of like direct all of our resources to giving ai more energy and power it's like um i mean no you would really you put a guardrail on yeah like obviously you don't want an ai ceo that is not governed by humans but if you think about if you think about maybe like

26:59this is a crazy analogy but i'll give it anyway if you think about a version where like every person in the world was effectively on the board of directors of an ai company and got to you know tell the ai ceo what to do and fire them if they weren't doing a good job at that and you know got governance on the decisions, but the AI CEO got to try to like execute the wishes of the board.

27:26I think to people of the future, that might seem like quite a reasonable thing. Okay. So we're going to move to infrastructure in a minute, but before we leave this section on models and capabilities, when's GPT-6 coming? I expect, I don't know when we'll call a model gpt six uh but i would expect new models that are significant gains from 5.2 in the first quarter of next year what does significant gains mean i don't have like an eval score in mind for you yet but uh more enterprise side of things or definitely both the there will be a lot of improvements to the model for consumers uh the main thing consumers want right now is not more IQ.

28:11Enterprises still do want more IQ. So we'll improve the model in different ways for different uses, but our goal is a model that everybody likes much better. So infrastructure. You have 1.4 trillion thereabouts and commitments to build infrastructure. I've listened to a lot of what you've said about infrastructure. Here are some of the things you said. If people knew what we could do with compute, they would want way, way more. You said the gap between what we could offer today versus 10x compute and 100x compute is substantial. Can you help flesh that out a little bit? What are you going to do with so much more compute?

28:53Well, I mentioned this earlier a little bit. The thing I'm personally most excited about is to use AI and lots of compute to discover new science. I am a believer that scientific discovery is the higher bit of how the world gets better for everybody and if we can throw huge amounts of compute at scientific problems and discover new knowledge which the tiniest bit is starting to happen now it's very early these are very small things but you know my learning in the history of this field is once the squiggles start and it lifts off the x-axis a little bit we know how to make that better and better um but that takes huge amounts of compute to do so that's one area we're like throwing lots of ai discovering new science curing disease lots of other things um a kind of recent cool example here is we built the sora android app using codex and they did it in like less than a month they used a huge amount one of the nice things about working at open eyes you don't get any limits on codex they used a huge amount of tokens but they were able to do what would normally have taken a lot of people much longer and codex kind of mostly did it for us and you can imagine that going much further where entire companies can build their products using lots of compute um people have talked a lot about how video models are going to point towards these generated real-time generated user user interfaces that will take a lot of compute um enterprises that want to transform their business will use a lot of compute.

30:28Doctors that want to offer good personalized healthcare that are like constantly measuring every sign they can get from each individual patient, you can imagine that using a lot of compute. It's hard to frame how much compute we're already using to generate AI output in the world. But these are horribly rough numbers. And I think it's like undisciplined to talk this way, but I always find these like mental thought experiments a little bit useful. So forgive me for the sloppiness. Let's say that an AI company today might be generating something on the order of 10 trillion tokens a day out of frontier models.

31:15You know, more but not. It's not like a quadrillion tokens for anybody, I don't think.

31:24let's say there's 8 billion people in the world and let's say on average someone's these are i think totally wrong but let's say someone the average number of tokens outputted by a person per day is like uh 20 000 you can then start to and the token you could to be fair then we'd have to compare the output tokens of a model provider today not not all the tokens consumed but you can start to look at this and you can say, hmm, we're gonna have these models at a company be outputting more tokens per day than all of humanity put together. And then 10 times that, and then 100 times that. And, you know, in some sense, it's like a really silly comparison.

32:07But in some sense, it gives a magnitude for like how much of the intellectual crunching on the planet is like human brains versus AI brains. And that's kind of the relative growth rates there are interesting. And so I'm wondering, do you know that there is this demand to use this compute? So for instance, would we have surefire scientific breakthroughs if OpenAI were to put double the compute towards science or with medicine? Would we have that clear ability to assist doctors? Like how much of this is sort of supposition of what's to happen versus clear understanding based off of what you see today that it will happen?

32:52Everything based off what we see today is that it will happen. It does not mean some crazy thing can't happen in the future. Someone could discover some completely new architecture and there could be a 10 ,000 times efficiency gain and then we would have really probably overbuilt for a while. But everything we see right now about how quickly the models are getting better at each new level, how much more people want to use them. Each time we can bring the cost down, how much more people really want to use them.

33:21Everything about that indicates to me that there will be increasing demand and people using these for wonderful things, for silly things.

33:36but it just so seems like this is the shape of the future it's not just like it's not just you know how many tokens we can do per day it's how fast we can do them as these coding models have gotten better they can think for a really long time but you don't want to wait for a really long time so there will be other dimensions it will not just be the number of tokens that that we can do but the demand for intelligence across a small number of axes and what we can do with those you know if you're like if you have like a really difficult health care problem do you want to use 5.2 or do you want to use 5.2 pro even if it takes dramatically more tokens i'll go with the better model i think you will um let's just try to go one level deeper um going to the scientific discovery.