We Interviewed Sam Altman at TreeHacks 2026

Stanford memories

00:00All right, everyone. Um, so how many of you uh are Stanford students? Raise your hand. Okay, pretty good. We got a lot. Um, how many of you in your like years at Stanford lived in Donner? >> We also got a few. >> I think we got [laughter] a few. >> Well, Sam was actually a Donner resident and uh yeah, so why don't we start there? Do you remember moving in on your first day at Stanford over here? >> I do. I actually I haven't been back to campus in so long. I'm feeling inspired to like go walk by after this cuz I have like such fond memories of that first day. Um it was like, you know, I'm sure like for all of you it was a very strange experience, but it was like awesome as soon as I got here.

00:41>> Do you have any favorite memories? Any building climbing, tunnel diving? >> Uh yeah, I I was mentioning this backstage. I like it's sort of, you know, when you go to a place you haven't been in a while, all these memories that you forgot about come come back. Uh, and very near here, uh, like early in freshman year, a bunch of us went steam tunneling, which I don't know if people still do, but was like a cool right of passage at the time, uh, one of the people that we went with was like not told you had to put the cover back on. So, they kind of left the cover off. We went down and looked around and whatever and came back and there was a car, professor's car that had like fallen into the open manhole. Uh, I thought I

01:22was going to get like, you know, kicked out. it was like first few weeks of school. Um, but I had totally forgotten about that and it's fun to see. Um, my memories are like Stanford is awesome. Uh, and I just have like very happy memories of that time. Uh, and kind of even the parts that I didn't think I was going to like at the time like staying up all night working in like the basement of Gates are very happy memories now. >> I think that's like a core CS student type of thing. I have also pulled all nighters in Gates. It's >> there. It's a good memory in retrospect. >> Yeah. And every time I walk by Gates, I just think back to that all nighter and uh you know, Gates Gates comes with certain memories now. [laughter]

02:03>> Yep. >> Did you have any specific clubs that you were a part of here at Stanford? >> Um I did a few, but the honestly the most the best thing I did was just like hacking on projects with friends. Like that was if I could go back and do it, I would have done like less clubs and more just building stuff. Yeah. All right. Um, well, we went through the archives uh of Sam's time here at Stanford, and I don't know if you guys know the, uh, club faces. It's the student entrepreneurship club here on campus. And they found this document, the business symposium. Um, whoa. And it was for the next [laughter] generation of business leaders. So, this is from spring 2005. This is like right before you dropped out. Uh and in this document

First startup and YC

02:50there's this one entry uh and it says Vienno and Viendo is a service for cell phones that provides personalized information about hot venues, a map of locations of friends nearby and compatible new friends and dates in the area. And keep in mind this is 2005 so this is like before the iPhone came out. So this is kind of like a crazy idea at the time. Uh, and it's co-founded by four students as you can see here. Um, Peter, Alec, Nick, and, uh, this guy named Sam up there as well. Um, is this looped? >> Yeah. Uh, I forgot about this also, but the the important thing here is not about building stuff, but it's about how much Y Combinator did to change what it took to get a project funded. Um, I was

03:39like, you know, I came here, I was not that interested in startups and then it kind of like I was like it was in the water and I got excited about startups, but it was a super different time then. And you would like talk to people and they'd be like, "Oh, you need like a business person. You can't just you got to like get these connections to VCs. It was like, you know, you got to like get serious. You need like a bunch of MBAs. You got to write a business plan. And, you know, it's like you need to like raise this big round and you're going to have these VCs. They're going to tell you what to do and whatever." And I was like, "Okay, I guess I don't know any better." And these smart people are

04:11saying that's what you have to do, so like I'll believe it. Um, this was right around this time is when Y Combinator launched. Uh, and I'm sure you all already think this from just hearing from Gary, but like if you want to start a startup, you should definitely do Y Combinator. Uh, but and it's an amazing thing. Uh but before YC like in the dark ages, this is what you had to do. Like you had to go do business plan competitions which are a business plans are a waste of time. Business plan competitions even worse waste of time. Um but this is kind of what you were stuck with. Like this was how you could get things out in the world. And in the 20 years since uh things have changed like unbelievably for the better.

04:56>> Yeah. So how long were you working on this idea before like you discovered Y Combinator? Uh I was like hacking on like a project. That was another thing like it didn't this like many other things did not start intending to be a company in any way. This was like a sort of late night dorm project. >> Oh wow. >> But over like a while and then it got serious when YC >> you remember if you won this competition. >> We did. Yeah. >> That's pretty good. >> Um so then how did you end up getting in contact with like YC? You were in the first batch, right? >> Um you just like applied online. I actually I think it was maybe it was like you filled out this weird form that PG had that you had to like paste into an email and not change any

05:37formatting because he had some weird parser for it. I think it was like that. >> So all three of us are sophomores right now. Um could you walk us through a day in your life back then? >> Um I mean it was really boring like there like >> [laughter] >> I don't know. I like went to class or didn't and I like hung out with my friends and I built stuff >> like Yeah. Again, very fun memories, but it was like very like simple, lovely, boring time. >> Yeah. >> So, when you were considering dropping out, did you feel like it was it was risky? I mean, were you excited? I mean, it sounds like school maybe wasn't the whole uh environment that you were looking for. What was kind of like your your process behind that?

Dropping out and raising $30M

06:27Uh, look, I feel a little bad saying this because obviously it worked out for me and I don't, you know, survivorship survivorship bias is a real thing. >> Uh, I didn't think at the time and I don't think now that dropping out is like a particularly risky thing to do. >> Uh, I don't know if Stanford still has this, but at the time it was like you could stop out for eight years and come back kind of no questions asked. um which I think is a great a great policy and it certainly made it easier to get my parents slightly on board with the idea. Um I think you should just work on whatever the sort of most interesting highest rate of learning highest impact thing you can is. And if that's being in school and learning a ton of stuff and

07:14being around interesting people and working on interesting stuff, great. If it's doing a startup, great. if it's dropping out to do AI research or whatever. Also great. Um I think one of the trends of the last few decades, couple decades at least, has been that um the default path has gotten relatively less good. And the option space of what you can do and still be really successful and happy and have a great impact on the world has increased and increased and increased. And as the society gets richer and freer and more capability with a better technology tree and like I think that will just keep going. So uh it didn't feel like a crazy or risky thing to me at the time. Uh I think if I were a student today it would

08:04feel like even more of a that's totally something I could consider. >> Yeah. >> My parents didn't like it. >> Yeah, that makes sense. That makes sense. Wow. So you raised over like $30 million for this idea which you know is like kind of considered like seed round today. How >> I mean I was going to say that's like a pre pre [laughter] like it was a lot of money at the time. >> Yeah. Um how how did you do this? I mean what what did >> 17 GPUs now or something? >> Wait. No exactly right. >> Well one thing that was is cool about Stanford and particularly so at the time is it had like a good on-ramp. It was like very well connected to the whole like VC machinery. >> Yeah. and Y cominator also was helpful

08:44there. >> Yeah. >> Um it was maybe there were less VC firms and less money at the time but they were extremely focused on Stanford as like a source of ideas and people. >> Do you remember any like stories uh from that YC batch or from founding? Like did it go really well all at first or like what was that process like? Um, actually it felt like still being in college. Everybody was like pretty young at the time. Um, we kind of like would stay up late talking or working on computers and it it it felt like it felt shockingly not that different. And I've heard a lot of people say this that have done YC or not that have dropped out to do startups. Like if you're a college student kind of like if you're like a CSish college student and

09:35then you do a startup the fir like the last year that you did school and the first year of doing a startup eventually it gets very different. They're like shockingly the same. >> So I mean we have a lot of students here from Stanford but we also have a lot of non-stamford students and I agree with you. I do think Stanford has a pipeline into like this PC culture and all this money, right? I mean what would you recommend to students coming from other schools if they were interested in going into this the same process? That was the case at the time. I think that's no longer the case. I think the sort of like Stanford special access I mean maybe there's still some of it but I think it's like mostly over maybe

10:08totally over maybe even slight negative selection for Stanford students at this point. Um the I think YC did a lot for this but also like VC just matured as an industry and there's so much money in the world that wants to fund startups now. Um that I think it's no longer the case at all that it's like a very Stanfordy thing. Okay. So, fast forward a few years and you're now the president of YC and then all of a sudden, boom, open AI is born. Um, what happened? How did you guys come up with the idea? >> Uh, so I was studying AI when I was here and it was not working at the time at all. Like I thought AI would be the coolest, most important thing, but it was I worked in the AI lab the summer between uh my freshman and sophomore

Origins of OpenAI

10:54year and I was like, okay, these are this is not it. Um, and I got distracted and did a startup with something else and then I became an investor for a while. But I always thought that uh AI was at least one of the two or three most important things that could happen. Um, and you know, I was like paying attention to it. I This is like a a thing I recommend and something I have heard many people describe over the course of your career, which is you get conviction on the things that you care about early, a super set of them. Some you'll lose interest in, some will develop more than you thought, but the the landscape of the world just is going to keep changing as you get more experience. And continuing to focus and like stick your

11:41head up and look and not get into tunnel vision on one thing seems like it's really important and really correlates with success over a long period of time. And you know, so I was like paying attention to all the areas I was interested in. In 2012, uh, the Alex Net paper happened and I, like everybody else, was like, "Oh, that's kind of cool or very cool, but it didn't update me as much as it should have." Like, you know, strong priors are a real factor. I I then watched over the next couple of years as it deep learning models kept getting better with scale and I still didn't update enough but now I was at least like this is like an asteroid coming and a crazy thing that people are not paying

12:27more attention to and so in 2014 we started saying you know we should really do something about this. Um it was incredibly unpopular at the time. Like we had said we want to make an AGI lab and all the like elders of the field were like you're insane. You're a scammer. This is like you know AGI is 100 years away. None of these approaches are going to work. And we really said let's just push on this one idea that scaling deep learning seems to matter. We didn't know at the time how beautifully predictable the scaling laws were, but it was at least clear back in those days that if you threw more compute at something, you got better results most of the time. Um, and we kind of just decided we were

13:06going to push on it as far as we could and see what happened. Uh, we were also very worried about what it would mean for like how we were going to solve the alignment problem, what it would mean for society. We didn't know that we were going to make a product. We just thought we were going to be a research lab. So, we kind of had a weird start. Um, but it was really this it was this mindset of if AI works, it will be unbelievably important and we finally have an attack vector that maybe can go very far. It felt and still feels kind of crazy to me that it can go as far as it's turned out to go. Um, deep learning, the fact that these models can sort of do unsupervised learning in particular still seems sort of magical to me. The

13:50fact that next word prediction can be used basically to discover new scientific ideas. It makes like intellectual sense, but to see it work is still like a very crazy thing. Um, but that was it. It was we have this one idea, let's push on it. >> So, you see all these ideas now, but as you mentioned, it was incredibly unpopular at the time. I'm really curious to know what the first pitch for OpenAI looked like. >> Um, I love the unpopular ideas. I I I have always liked ideas that are big if they work, difficult to get to work, and unpopular. Um, my career as an investor was basically betting on those. Uh, for whatever like reason that people think one thing is fun and not another, this is something that has always seemed

Early days and GPT moments

14:37particularly fun to me. So, even if it weren't that I loved AI so much, I would have thought the fact that this seems really undervalued and promising uh was was cool. And that was basically the pitch. The pitch was uh something important is happening with deep learning and scale. Uh we don't know what we're going to do with it. We don't know where it's going to go. We had a bunch of ideas that turned out to be wrong on the hops along the way, but we're going to push on this and something good is going to come out of it and other people are undervaluing this. So it was a it was like that was really the pitch. It was not a great pitch. [laughter] Well, it worked. Um, how did you meet your co-founders?

15:20>> Uh, I had known Greg forever. Um, he I was an early investor in Stripe. I think he was the first employee and I was like brought in to help close him. Um, and we had stayed in touch for the sort of decade or whatever in between. Um, Ilia is the sort of genius and godfather of the field and I stalked him at a conference. Uh and then later we started talking about um doing a startup. Uh Voytech I met through kind of the like weird AGI nerds network of the Bay Area at the time and John one of the others connected me to and Elon uh I guess yeah. [laughter] So, so how did founding feel on this time with OpenAI compared to your experience with Looped before? >> Uh, I mean this was really a weird one.

16:17Like I the degree to which OpenAI was not meant to be a company is like very hard to overstate. We had no idea that we were going to ever do a product. >> Yeah, >> we thought we were just going to do research papers. Um, as we got going, it became clear that a there was going to be a lot more economic value along the way than we thought. We kind of had this conception that you were going to build this super intelligence and you're going to have this like crazy thing happen all at once. And we learned that was not quite the right picture. We also realized that instead of needing the few billion dollars we thought we might need, you're going to need like hundreds of billions of dollars. >> And so it evolved, but at the start it

16:58was like we're going to be a research lab. actually one of my most vivid memories of OpenAI. Very first day been all this drama to get it started. Uh very first day we're together in Greg Brockman's apartment which was where we worked until we got our first office a few weeks or maybe a month later. And it's like, you know, 9:30, 10 in the morning. Everybody rolls in. We're sitting on Greg's couch. Maybe there's 10 or 12 of us. Maybe not even that many. Maybe eight or 10. And we look around and say like, "Okay, what are we going to do?" >> Yeah. >> And someone said, "We should write some papers." And someone said, "Okay, we need a whiteboard to start talking." >> And like someone orders like a

17:38whiteboard on, you know, Amazon. >> Yeah. >> Instant or something. >> And and I had this real moment of like, what? This is not this is not good. Like I don't know what this is, but this is not a startup or any kind of thing that's going to be effective. Um, but you know, I like I am a big believer that in moments like that, you just like breathe, trust that if it's if you have good people around, it's like going to work out. And we just kind of went with it. Sometime in that first week, most of the ideas that turned out to be the core ideas for the um first four years of OpenAI were written down on that whiteboard. Even though at the time we didn't realize that and we're kind of just like, eh, this is probably not. We

18:19went in some other directions. And you know, we said we need to get some GPUs, we need to do this, we need to do that. Uh we need to like pick some projects to see if this is really working. >> And stuff just kind of kept going. >> Wow. >> Yeah. So you're uh you were in this place where you're like, "Okay, what do we do? Let's start doing some research papers." like when was the moment after that where things started to click for the first time and you're like uh things started to feel like uh you guys really had discovered something or something was like big was about to happen. Um

19:01there were a few moments I think it was not just one but the the felt sense was it was like miracle after miracle and so at some point more than any one thing that worked. It was like, man, something about the underlying approach here feels like we've discovered like a new law of physics or something. And you know, it was like great to get Dota working or the robot hand working and then eventually the the first language model. But the the biggest takeaway was just like there is something about this underlying approach that really feels like we're on a trajectory to the degree that I had like a single moment. It was the GPT series. Um like by GPT2 it was clear to me like man this is gonna this

19:48is something important is about to happen. >> Do you remember that day the GP G2 launch? >> I do. Uh I don't remember the launch day but I remember the day that like I got to first talk to the model and I was just like wow this is this is great. And actually I think it was technically a model that was like a little bit beyond what we released as GPT2. Um, but like I knew GPT3 would be amazing and GPT4 would be amazing and they were and they were amazing in new ways. But that first night that I got to play with the model and it was like doing something I never had seen a computer do before. I was like, "Okay, this is and and we had the builtup like confidence of deep learning working." >> Yeah. And you initially withheld that

20:33model GBT2, right? What at what point did you feel like we were ready or or like what made you decide that the world was ready for these models? >> Uh look, clearly that looked like silly in retrospect. I think the principle of precaution with each new level of AI capability is reasonable. Alignment has been easier to make progress on than many of us in the field thought. Uh but the societal impacts have been or are getting big. Um, and you know, if we bias like slightly too much towards the cautionary side, I think that's good. Uh, too much would be bad. I I'm also worried about like a mega AI capability overhang building up. Like the way I would explain this is if companies don't adopt AI fast enough then they will lose

21:27to fully autonomous completely AI run and started companies and that will be a crazy destabilizing thing for society. So you can't be that cautious either. Um but you know like we'll go a little bit on that side of the line. >> So what do you think the next chat GPT moment will be? Uh well I think the next JBT moment already was coding agents. Um and I think the next one after this that has not come yet will be that same level of ability to get stuff done for all knowledge work which I don't think is that far away. >> Wow. So I mean we're all sophomores here. Um there's a lot that's going to change in the next few years. I mean before we graduate I think. Do I mean do you think AGI will be >> Yeah, I think if you are a sophomore

AGI predictions and societal impact

22:16now, you will graduate to a world with AGI in it. Uh and it will be much, you know, in some ways it'll like be the same. You'll go move and get a job and think about having a family and whatever else like the human, you never bet against like sort of the human drives and what we care about staying the same. But in some other sense, it's just going to be wildly different. uh you know I think we'll have AI uh improving at an incredibly rapid clip. Um society will be coming along uh at a slower clip but still very fast. Science will be getting automated. Uh what it means to start a startup will be totally different. What it means to go work at a company will be totally different. Uh there's going to be a lot of change in

23:03the next couple of years. Uh you are lucky to be a student right now because you can go do kind of whatever. uh and you can try a lot of things quickly. Um but and you're also lucky in that this is probably like the most interesting time to be starting off like adult life or a career. Um but I think a lot of the traditional advice is not quite going to work. >> Yeah. So speaking of execution, um in your first ever blog post on blog.samalttman.com, sam alman.com. You say that knowing is easy and it's the doing that's difficult. Um, is there a truth that you think you know now about the future where the missing piece is execution? >> Um,

23:55well, I think that's just generally going to continue to be true. Uh, I mean, knowing knowing is easier and easier like you can you get the help of these AI tools. Um, getting stuff done is easier too, but it it's easier for everybody. And so you have to like compete with everybody else trying to get stuff done in the world. Um, the it is for sure true that what one programmer can do now uh is like mindbendingly different than what you could do a year or two years ago, a year ago, let's say. Um, it is also true that the people that I know that are using these tools the most effectively say uh it has never been harder to do their work. And I suspect this trend is going to keep going. But like man, watching these

24:43people who are really good at using AI coding tools have like 12 agents running all the time and like these complicated custom harnesses that they're constantly evolving like the the yeah, the tools have gotten unbelievably good. Um, and the ability to use them to be at the top of the game I think has never been harder. >> And you think this will apply across like all verticals, not just coding? >> Uh, I mean, look, eventually you will just say like, "Hey, Mr. AI, please like make me my whole startup and do everything and do a great job. You know, I'll help you with whatever you need." But between now and then, yeah, I think it'll apply to all all verticals. Given that uh these models are becoming

25:24more and more powerful then and you you we have people that are running this many coding agents. There's definitely some of y'all in the audience here. Um what should people be working on and focusing on then? Like what do you think is the most important problem in the world right now? >> Uh

25:45the the degree to which it feels like everything is up for a rethink. I'm not like that interested. People are like, "Oh, all SAS is dead. I'm gonna like, you know, make a new startup to make SAS company X better." Like, you know what? That will probably work. But I think that's missing the point of what's possible. Now, the degree to which things are just completely fundamentally reimaginable, uh, and the space feels super open on that. like you know if you like just to pick a random example uh social products have not changed that much in the last and I'm not even counting like video scrolling apps just like an actual connect to people and like look at information about them style apps have not changed that much. I

26:38think uh moldbook points to the first interesting new thing where you can imagine a bunch of agents on behalf of their users off in a virtual space talking to each other like exchanging new information completely changing what it means to interact with other people on the internet like that was just not possible at all until very recently and now it feels like the space of social for the first time is totally open for some startup to do something completely new. Um, you know, a lot of people are like bolting AI into some productivity software and you know, like I don't really need something in Google Docs trying to like summarize it or write a sentence for me. I mean, that's like fine, but probably the whole thing of

27:19what it means to write a document is going to completely change. And there's a whole new kind of thing to imagine there. And this will apply not just traditional software startups, but most companies in the world pretty soon. You know, robots won't be that far off, whatever. Uh, I love times like this. They're rare. The iPhone when iPhone launched was one of them. I don't think we've really had one since. And the fact that this time, not only can you use the technology to do these things that you could never do before, but the fact that you can use technology to like make the product or make the company so quickly and with so few people, I think it's going to mean a lot more startups getting super successful really

28:04fast. And a lot of startups that have like one person or six people or something like that that get as impactful and as much revenue as some of the you know a medium-sized company does today. Do you think then that uh given you were talking about uh like Mbook these agents that like once AGI happens it will then surprise us and just all of a sudden like all of everything we've done all these new companies are popping up and creating themselves and integrating into our world and competing with things in a way like that or like how will it be introduced into our world then >> uh so I think I think that what it's going to feel like in the next few years let's say two years is stuff's just going to

28:52happen faster. You know, startups are going to do new things faster. Existing companies are going to ramp their revenue faster. It will feel like we've broken the laws of traditional speed and product development and business growth rates and and things like that. And, you know, companies will start to hire AI co-workers um and do amazing things with fewer people. Uh, I I think we'll continue to see AI research go much faster. Um, and we'll see scientific research happen much faster, but I don't think it'll feel like totally autonomous companies transacting with each other in an environment sort of moldbook style. Uh, eventually that probably does happen. Uh, and you know, one of one of the sort of

29:37like central observations I've had in life is that people are unbelievably adaptable. Societyy's unbelievably adaptable. So that sounds like a totally crazy destabilizing thing. And I bet it's not going to be as weird to live through as it sounds or only for a day. >> So I kind of wanted to go back to that thing that you'd mentioned about societal impacts. I mean, how do you think this is going to impact like politics like religion? like just expanding more just outside of like the startup space. How's society going to be impacted by this? Do you feel >> one of the um everyone's got a different definition for AGI, different definition for super intelligence. Uh you know, I kind of think like the most important

30:18definitions are something about the ability to self-improve. But one of the ones I like as a sort of example for a way to think about this is if if we had an AI system that could do a better job at making decisions than anyone we could possibly have be say president of the United States. Uh would we and like confidently much better. >> Um would we politically or society want that? >> It's very unclear. uh you know most people I think today at least would say probably not. Um maybe as things evolve more they do or you know like an AI CEO of a big company would would you rather have uh I think it'd be awesome for open AI to have an AI CEO but I think a lot of people be like ah that's a little that's a little scary. Um,

31:10if though AI is better at doing some of these things, I think there will be like many things that people are better at than AI long term, or at least people really care about other people doing, but I have no delusions that an AI will not be a better CEO of OpenAI than me at some reasonably soon time. Um, if if that's true and if some companies or countries don't do that and others do and AI is much better like that will have a real impact in economic competitiveness, national competitiveness, things like that. And and so I think one of the things that will happen about how this is going to impact us economically, society, politically is if the AI is just much better, I think people will feel increasingly like we

31:58either do worse or we put the AI in more and more influential positions. I think people will always like, you know, if you think of like an AI CEO of a company, I think people will always want human board members and that's probably a really great idea. Um, but I kind of think that people may have not quite I certainly have not really wrestled with like is there a way that this doesn't happen and what all of the political, economic, societal impacts are. Uh, I I still believe that although it sounds like a completely crazy thing to say, we're very adaptable. We really care about other people. You know, maybe there's like a AI CEO, but you just care about like the company's spokesperson speaking to you in these

32:51like 8second video clips or whatever. >> Um,

32:59>> I think I'm not a jobs doomer at all. I mean a lot of the current jobs are going to go away or be heavily changed but human desire for being useful to each other to compete with each other uh to like create differential status to do something fulfilling to express creativity that is not going to go anywhere. And maybe maybe the jobs of 100 years from now look nothing like the jobs of today. >> Yeah. nor do that many of the jobs of today look much like the jobs of a few hundred years ago. Um, but I'm confident we'll have stuff to do. I'm confident we'll really care about other people and less about the machines. And then beyond that, uh, yeah, I think we're just like AI is going to get ever more competent and

33:47we're going to have we're gonna want to use it for more and more things. >> Awesome. All right, so we're gonna go into a quick Q&A segment now uh, with questions from the audience. I would love like hard questions that I've never heard before. We have a Slack channel, Sam Alman Q&A. >> Sam Alman Q&A, guys, and a lot of you have put in questions. Um, >> so we're going to we're going to start off by reading some of the questions that were already submitted, I think, since we posted it yesterday. But we encourage you guys to submit more questions and then if you really really like a certain question, we want you to just uh reply with some sort of emoji so that we can see it and we can ask Sam. Awesome. All right. You want to start

Q&A: competition, cash burn, happiness

34:24off >> to get started? Uh, you're talking about like OpenAI potentially having a AI CEO. So, if you ask a question that's kind of related to this about like say OpenAI becomes this like end- all beall company that can do anything because it's uh CEO is an AI. How do you compete with OpenAI then in in the future? Um, when we started OpenAI, everyone was like, you can't do this. You can't compete with Google. It's impossible. And there will someday be much bigger and more successful companies than OpenAI. They will not do exactly what OpenAI does. Uh you may steal our users. You may do some other thing. You may like have a replacement product. It will not very unlikely to be exactly what Open AAI does. Uh

35:08Google screwed up, didn't react enough to our approach early enough. They're, you know, doing a very nice nice job now, but had Google had their act together, we would not have been able to get off the ground at all. Um and they had very smart people. It's just big companies have big company problems. Uh someone in this room I hope will do the same thing to OpenAI. We are in we sell intelligence for what I think of as a very low price. Um you have probably the biggest option space of any startup of any of startups that have at any time in history. If if you try to make like an exact copy of chatbt or codecs or you know frontier models in an API probably not going to work. There's so much other stuff to do. Uh and the

36:03best thing of all is to figure out you know we talked about this earlier like things that are just going to totally change now. Take your pick. We're not going to be able to go do all those things. Uh, and neither is any other company that is not a startup and that has the sort of like freedom to be a little bit weird and decisive and pull together a band of rebels. Just go do that. It always sounds really scary. I remember how many like very wise people said you can't start an AI company. Google's just going to crush you. Uh, maybe they still do. I don't know. Um, but just just like go at it. >> Um, okay. Well, I can ask the next question. Um, this might be a burning question. Let me see. All right. News

36:45reports say OpenAI is burning cash very fast and could face liquid liquidity pressure in the future. How do you plan to handle this? And is the situation really as serious as you think the media reports it to be? >> Uh we are burning cash very fast. It is not a serious situation like the you know if we can spend a billion dollars this year to make $3 billion next year there's a lot of capital in the world that wants to do that. So we will raise a lot of money equity and debt. we will spend a lot of money. We'll make a lot of money. Uh the it's weird. The economy hasn't seen something quite like this before, but given what we see about revenue growth and model growth and how much model growth correlates with future revenue

37:29growth, we're like, yeah, super confident in where things are going to go. >> Yeah. >> So, we've got another question here. It's um Sam, are you really happy >> [laughter] >> I I am actually one of the happiest people I know. Uh but I didn't used to be. I used to be a very anxious person. Um the [snorts] a thing people say to me all the time is like you have a miserable job. You have all the stress. You have all these people coming after you. You have like crazy bad You know, so many things happen to you a day. Like how do you not have a mental breakdown? Um, and my answer to that is like I just figured out what it was going to take for me like in my 20s when I realized I was not particularly happy and certainly not

38:19particularly calm. I figured out what it was going to take for me to get happy and calm. Um, I think people find their own paths there. But, uh, meditation was a big part of it for me. Uh, and it's kind of like a onetime thing. And now like even when stuff is really hard, like really painful, um, one of a thing I kind of learned in meditation that always stuck with me is that everybody thinks the opposite of a bad experience is a good experience. So if I'm having a bad experience, then I'm not happy because I wish I were having a good experience. And the kind of like a big mental shift for me was to reframe it as the opposite of a bad experience is no experience. And someday that'll happen to you and

39:07you'll miss the bad experiences too. And you know like I have a lot of days where it's very stressful and very hard and a lot of things go wrong. Uh I'm still grateful for them. >> Adding on to this um someone asks what does a day in your life look like then? >> Um absolute chaos. Uh I I like wake up early. I work for a few hours. I can I kind of have control of my life until like 8 o'clock in the morning. Uh and I can like get something done. I can try to drive whatever I'm want to get done. Then I play with my kid for an hour. Then I go into the office. And then it's just like insane. Whatever is going to happen happens like crazy. I don't think any company has been as fastm moving, chaotic in everybody's

39:58crosshairs as us. And so it's just yeah, unpredictable chaos all day. >> Yeah, a lot of us definitely don't wake up at uh before 8 in the morning. >> I did not used to wake up early. This this this job is the thing that made me start doing it. >> Awesome. >> Should we do two more questions and then >> let's do two more questions and then we'll wrap up. >> We are at time. I I have another question from someone. Um, what AI sub field today feels like open AI in 2016 a little undervalued or underestimated but could shoot out of nowhere? >> Uh, that's a good that's a great question there. This is the kind of question that I would like spend a lot of time trying to think about. Uh, I'm not sure if you mean it as like a

40:42research thing or a company thing. Uh, I'll answer both and I'll do it quickly because I know we're almost out of time. Um, on the research perspective, I bet there is another new architecture to find that is going to be like as big of a gain as transformers were over LSTMs. And I think you finally have models that are smart enough to help do that kind of research. So I would I would go look for like where can I find a mega breakthrough uh and I would use the models to help me on the product side. I guess we talked about this a little bit earlier, but I would I would just pick a big area and say what is possible now with AI that wasn't possible at all before. like where can I totally redo something that's like AI is the absolute

Hardware and closing

41:37core to the the interaction working and look I don't want to say this is like a once in a-lifetime opportunity because I hope the world keeps getting dramatically better every few years and that if we all came back here or actually when some of you come back here and sit up here and talk to the then current students um AGI will uh look like just a warm-up for whatever the next important thing was and that'll keep going for the rest of history. Um, but this is at least the best time ever so far. And what what you can do now is so crazily exciting that I think you should probably try to figure out how to take advantage of this moment. >> Yeah. >> And one last question. Um, a lot of labs like XAI and Google have their own data

42:28centers and even custom silicon for inference. Does OpenAI have any interest in developing hardware as well or stick to external partners? Why or why not? >> Uh we have a big custom silicon program. Um we we're very excited about our uh our inference chip and clearly the world wants a lot of cheap tokens and I think what we're working on there will be great. We have a very deep partnership with Nvidia. We do all of our training on Nvidia. We also use them for a lot of inference. Um but we are excited to be doing uh our our chip in our system. Um building data centers I would love to not have to do that. [laughter] Um if we have to at some point we will. Uh that's you know like you can't do everything well as a company and that's

43:18like a big intensive thing to do. Um if we can just design a great rack and have other people operate those and build the crazy buildings around them that'd be awesome. Thank you, Sam. Everyone, let's give it up for Sam. >> Thank you. [applause]