How To Build The Future: Sam Altman
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We said from the very beginning, we're gonna go after A G I. At a time when in the field you weren't allowed to say that because that just seemed impossibly crazy.

I remember a rash of criticism for you guys at that moment.

We really wanted to push on that, and we were far less resource than demand and others. And so we said, okay, they're gonna try a lot of things. We've just got to pick one and really concentrate.

That's how we can win here. Most of the world still does not understand the value of like a fairly extreme level of conviction on one bed. That's why i'm so excited for starts right now IT is because the world is still sleeping and all this is such an astonishing degree.

We have a real treat for you today. Sam altman, thanks for joining. thanks.

This is actually a reboot of your series, how to build the future. And so welcome back to the series that you started years ago. I was trying think about that.

Yes, that's well, glad be rebut. That's right. Let's talk about your newest essay on the age of intelligence. You know, is this the best time ever to be starting a technology company?

Let's only say this time yet. Yeah, they'll be even Better times in the future. I sort of think with each successive major technological revolution, you've been able to do more than you couldn't.

And I would expect the companies to be more amazing and impact for and everything else. So yeah, I think it's the best time yet. Big companies have the edge when like moving slowly and not that dynamic. And then when something like this or mobile or the internet or semicon induct revolution happens, or probably like back in the days of the industry revolution, that was one upstarts have their edge. So yeah, this is like, and it's been a while, something to have this so this .

is like that pretty exciting in the sa you actually say a really big thing which is asi super intelligence is actually thousands .

of days away me I mean it's our hope I guess whatever uh but that's a very wild statement.

Yeah um tell us about that. I mean, that's that's big. That is really big.

I can see a half where the work we are doing just keeps compounding and the rate of progress we've made over the last three years continues for the next three or six or nine, whatever you know nine years would be like thirty five hundred days or whatever. If we can keep this rate of improvement or even increased like that system will be quite cable in a lot of things.

I think already, uh, even a system a one is capable of doing like quite a lot of things from just like our rock cognitive IQ on a closed end. Well define tasks in a certain area. I like a one is like a very smart thing, and I think we no need limited progress.

I mean, that was an architecture shift that sort of unlocked you a lot. What i'm sort of hearing is that these things are going to compound.

We could hit some like an expert, we could be missing something. But IT looks to us like there's a lot of compound in front of us still to happen.

I mean, this, say, is probably the most technical optimist of almost anything i've seen out there. Some of the things we get to look forward to, fixing the climate, establishing a space color, the discovery of all of physics, are near limitless intelligence and abundant energy.

I do think all of those things, and probably a lot more we can imagine or maybe not that far away.

And one of and I think it's like tremendously exciting that we can talk about this even so, I seriously now, and one of the things that I always have loved the most about yc is that encourages slightly implausible degrees of technical optimism and just a belief that like ah you can figure this out and you know in a world that I think is like sort of consistently telling people people this is not gonna, you can do this thing. You can do that. I think that kind of early pg spirit of just encouraging founders to like think a little bit bigger. IT is like IT is a special thing in the world.

The abundant energy thing seems like a pretty big deal. They're sort of path a and path b. You know if we do achieve abundant energy, IT seems like this is a real unlock. Almost any work, not just your knowledge work, but actually like real physical work, you could be unlocked with robotics and with language and intelligence on tap, like there's a real age of abundance.

I think these are like the the key to in the two key inputs to everything else that we want. There's a lot of other stuff, of course, that matters, but the unlikely would happen if we could just get truly abundant intelligence, truly abundant energy, what we be able to make happen in the world, like both like come up with Better ideas more quickly, and then also like make them happen in in the physical world. Like to say nothing of IT be nice to be able to run lots of A I and that takes an, uh, I think that would be a huge unlock in the fact that it's and not sure IT to be whether like whether to be surprised that is all happening the same time or this is just like the natural effective in increasing rate of technological progress. But it's certainly exciting time to be alive and great time to do start up.

Also, we sort of walk through this age of abundance. You know, maybe your robots can actually, manufacturer, do anything. Almost all physical labor can then result in material progress, not just for the most wealthy, but for everyone. You know, what happens if we don't unleash unlimited energy, if you know there's some physical law that prevents us from exactly that.

Solar plus storage is on a good enough trajectory that even if we don't get a big nuclear break through, we would be like OK ish. But for sure, IT seems that driving the cost of energy down, the abundance of IT up, has like a very direct impact on quality of life, and eventually will solve that. Your problem in physics.

So we gonna figure this out. It's just the question of when and we deserve IT. Uh, there's you know, someday we will be talking not about fusion or whatever, but about the dicon, fearing that will be awesome too.

Yeah, this is a point time. Whatever feels like abundant energy toss will feel like not nearly enough to our great grandchildren. There's a big universe out there with a lot of matter.

One of the switch gears a little bit to so you're earlier you're mentioning program who about us all together really created y combinator. He likes to tell the story of how you know how you got into Y C. Was actually you are stand for freshman and he said, you know what, this is the very first wisely back in two thousand and five and he said, you know what, you're a freshman and why you will still be here uh, next time you should just wait and you said, i'm a soft wore and i'm coming and you widely known in our community is, you know, one of the most formidable people. Where do you think that came from?

That one story, I think I would happy, be happy if .

I like just that on that was purely until zed.

my memory of that is that like I needed to be schedule an interview one day or something um and pg tried to like say like i'll just do IT next year whatever and then I think I said some nice version of i'm a soft more and i'm coming but then you know and you think it's like be awkward, it's only I don't and I say this was no false modesty. I don't like identify as a formidable person at all.

In fact, I think there's a lot of ways in which I really not I do have a little bit of a, just like I don't see why things have to be the way they are. And so i'm just gonna do this thing that from first principles seems like fine. And I always felt a little bit weird d about that. And then I I remember one of the things I thought was so great about Y, C, and still that I cares so much about Y, C, about is IT was like a collection of the weird people who are just like, i'm just going to do my thing. The part of this that that does resonate as a like, accurate self, I got anything, is I do think you can just do stuff, try stuff, a surprising amount of the time, and I think more, that is a good thing.

And then I think one of the things that both of us found that I see was a bunch of people who all believe that you could just do stuff .

for a long time. When I was trying to, like, figure out what mid wic so special, I thought that I was like, okay, you have this, like, very amazing person telling you, I you can do stuff I believe in you. And as a Young founder, that felt so a special, inspiring.

Of course, IT is. But the thing that I didn't understand until much later was IT was the peer group of other people doing that. And one of the biggest piece of advice I would give to Young people now is finding that peer group as early as you can. So important to me um and I didn't realize that was something the matter I kind of thought like I have you know i'll figured out of my own but man being around like inspiring peers so so available what twenty years both .

of us did spend time at stanford. I actually did graduate which is I provision have done that but I did that's great. You pursued the path of you far greater return uh by dropping out but you know that was a community that proportion dly had a lot of these characteristics. But I was still beyond surprised at how much more pot IT was with a ROM full of founders.

And I was say the same thing actually I like sad a lot yeah but I I did not feel surrounded by people that made me like want to be Better and more ambitious and whatever else. And to the degree I did, the thing you were competing with your peers on was like, who was gonna the internship at which investment bank? Which I mean, very sad. I fell in that trap. This is like how powerful peer groups are um it's a very easy decision to not go back to school after like seeing what the like Y C, I was like.

Now there's a powerful quote by carl Young that I really love um it's you know the world will come and ask you who you are and if you don't know that will tell you that sounds like being very intentional about who you want to be and who you want to be around as early as possible .

is very important. Yeah this was definitely one of my take ways of this for myself as you, no one is immune to peer pressure. And so all you can do is like pig good peers.

Yeah, obviously, you know, you went on to create looped, you sell that go to Green dot. And then we ended up getting to work the other at y talk to me about, like the early days of yc research. Like one of really cool things that you brought to Y C. Was this experimental.

And you sort of, I mean, I remember you coming back to partner rooms and talking about some of the rooms that you were getting to sit in with, like the little insurance ys of the world that you know, A I was some sort of at the tip of everyone's tongue because I felt so close. And yet IT was. No, that was ten years ago.

The thing I always. Thought would be the coolest retirement job is to get to I run a research lab and IT was not specific to A I at that time started talking my wife, he researched well.

Not only was I going to IT did and up funding like a bunch of different efforts, and I ish, I could tell the story of, like, I was obvious that I was going to work and be the thing, but I would try a lot of bad things to around that time, I read a few books, unlike the history of art park and bell labs and stuff. And I think there were a lot of people that was in the air of silicon bali, the time that we need to, like, have good research labs again. And I just thought I would be so cool to do.

And IT was sort of similar to what why c does and that you're gonna allocate capital to smart people. Sometimes it's going work and sometimes it's not going to. And I just wanted to try IT A I for sure was having a mini moment.

This was like kind of late twenty fourteen, twenty fifteen. Early twenty sixteen was like the super intelligence discussion, like the book S U E R. Intelligence was happening both me.

Yeah, the deep mind that have a feel like impressive results, but a little bit of a different direction. You know, I had been an A I nerd forever. So I was like, be so cool to try to do something was very hard. Was I out?

Yeah, yeah, for a while? Yeah, point. So you can telephone was a hot dog or not?

You could sometimes, yeah.

that was getting there. Know, how did you identify the initial people you wanted involved in Y. C. Research in opening eye? I mean, g greg brock, man was early.

in retrospect. Feels like this movie moontoast. And they were like all of these, like, you know, to be in like the bank is movie when you, like, drive around to find the people .

and they're like, you sound of a bit i'm .

in right like ill you I like heard he was really smart and then I watched the video of his and he's also, and now he's extremely smart, like true, true, genuine engineers and visionary. But also he has this incredible presence. And so I watched this video of his on youtube or something.

I was like, I got to meet that guy and I emailed any response. So I just like, some conferencing was speaking that we meet up. And then after we started talking a and then, like greg, I had known a little bit from the early stripe.

is what was that conversation like though? It's like, I really like what your ideas about A I and I want to start a lab.

yes. And one of the things that worked really well in retrospect was we said from the very beginning, we're going to go graph agi at a time when in the field you weren't allowed to say that because that just seemed impossibly crazy and you know, borderline irresponsible to so that got his .

attention immediately. He got all of the good .

Young people's attention and the decision duration, whatever that word is of the media or old people. And I felt like, somehow that was like a really good sign and really powerful. And we were like this rag tag group of people. I mean, I was the oldest by a decent amount. I was like thirty.

And so you have like these people who are like those are these irresponsibly Young kids who don't know anything about anything and they're like saying these ridiculous things and the people who that was really appealing to, I guess, for the same kind of people who would have said, like it's a, you know, on the software i'm coming, you know, whatever they were like, let's just do this thing. Let's take a run at IT. And so we kind of went around and met people one by one.

And then in different configurations of groups, and I kind of came together over the course of in fitz and starts, but over the course of, like, nine months. And then I started, I mean, and then I started, started happening. And one of favorite, like memories of all of open, I was.

So india had some reason, the google or something that we couldn't start in, we announced in december of two thousand fifteen, but we couldn't start in until eight, twenty sixteen. So like january third, something like that of twenty sixteen, like very early in the months, people come back to the holidays and we go to greece apartment, maybe there's ten of us something like that. And we sit around and IT felt like we had done this monumental thing to get IT started and everything like, so what do we do now?

What a great moment IT .

reminded me of when start up founders work really hard to like, raise us round and they think, like, I accomplish this and I use down and say, like, fuck. Now I gotta figure out what we're gonna.

It's not time for popping campaign e, that was actually the starting gun and now we got to around .

and you have no idea how hard the race is going to be. IT took us a long time if you get we're going to do. Um but one of the things that i'm really amazingly impressed by ellia in particular, but really all of the early people about is although he took a lot of twisted turns to get here, the big picture of the original ideas was just so incredibly right and so they were like up on like one of those flowcharts or White boys on our number which in grades apartment and then we went often, you know did some other things that work have didn't work or whatever some of them did and eventually now we have the slike system and IT feels very crazy and very improbable looking backwards that we went from there to hear with so many detours on the way.

But we are because deep learning.

even on that flip chat initially yeah I mean, more specifically than that, like do a big gun supervised model and then solve oil, was on the flip chart. One of the flip charts from a very, this is before graves apartment, but from a very early offsite. I think this is right. I believe there were three goals for the, for the effort of the time, I was like, figure out how to do on supervised learning, solve R, L, and never get more than one hundred and twenty people missed on. The third one is right, the like, the predictive direction of the first two, pretty good.

So deep learning. Then the second big one sounded like scaling, like the idea that you could scale. That was another horrendous idea that people actually found even offensively. You know, I remember a rh of criticism for you guys at that moment .

when we started. Yeah, the core beliefs were deep learning works and IT gets Better with scale. And I think those were both somewhat radical believes at the time we didn't know how predict be Better. I was scale that they didn't come for a few years later.

IT was a hunch first and then you got the data to show how predictable I was.

But the people already knew that if you made these that works or they got Better now um like that was we were sure of that now before we started. And what took the like where the keep coming to mind is like religious level of belief, was that that wasn't gonna stop. Everybody had some reason of, oh, it's not really learning.

It's not really reasoning. I can really do this. It's, you know, it's like a party trick and these were like the eminent leaders of the field.

And more than just saying you're wrong, they were like, you're wrong. And this is like a bad thing to believe, a bad thing to say. I was that there's got that.

You know, this is like, you're gonna perpetuate an air winter, you're gonna a do this, you're going to do that. And we were just like looking at these results and saying they keep getting Better, then we ve got the scale results IT just kind of breaks my intuition even now. And at some point you have to just look at the scaling laws and say, we're onna keep doing this and this is what we think it'll do in.

And also, IT was starting to feel that time like something about deep learning was just this emergent phenomenon that was really important. And even if we didn't understand all of the details in practice, which ibc we didn't and still don't, that there was something really fundamental going on is the P. G, S.

M. For this is we'd like discovered a new square in the period table. yeah. And so we just we really want to to push on that. And we were far less resource than demand and others.

And so we said, okay, they gonna try a lot of things and we've just got a pick one and really concentrate. And that's how we can we can win here, which is totally the right start up, take away. And so we said, well, we don't know, we don't know.

We do know this one thing works. So we're gona really concentrate on that. And I think some of the other efforts were trying to outsmart themselves in too many ways.

And we just say we'll do IT the thing in front of us and keep pushing on IT scale is the thing that i've always been interested in um at kind of just the emergent properties of scale for everything for startups. Turns out deep learning models for a lot of other things. I think it's a very unappreciated property and thing to go after. And I think it's you know, when in doubt, if you have means seem like it's getting Better to scale, I think you should scale up.

I think people want things to be less is more, but actually more is more, more is more. We believed in that .

we wanted to push on IT. I think one thing that is not maybe if that will understand about open eyes, we had just this even when we were like, pretty unknown. We had a crazy talented team of researchers. You know, if you have like the smart people on the world, you can push on something really hard .

yeah and they're motivated and or you created sort of one of the sole places in the world where they could do that, like one of the stories I heard is just even getting access to compute resources even today, is this crazy thing and is embedded in some of the criticism forms. Maybe the elders of the industry at the moment was sort of that you're gna waste a lot of resources, and somehow that's gna result in an AI winter, like people won't give resources anymore.

It's funny. People will never sure if we were going to waste resources or if we were doing something kind of vegal immoral by putting in too much resources. And you are supposed spread across lots of bets rather than like conviction on one.

Most of the world still does not understand the value of like a fairly extreme level of conviction on one bed. And so we said, okay, we have this evidence, we believe in this thing. We're gonna at a time when, like the Normal thing was we're gona spread against this bt nap ad and nap, you definitely optimistic, are definite optimist. And I think across like many of the successful he startups, you see a version about again .

and again that sounds right when the world gives you sort of push back and the push bag doesn't make sense to you, you should do IT anyway.

Told one of them many things that i'm very grateful about getting exposure to from the world of startups is how many times you see that again and again and again. And before I think, before I see, I really had this deep belief that somewhere in the world there were adults in charge, adults in the room, and they knew was going on, and someone had all the answers, and, you know, if someone was pushing back on you, they probably knew was going on.

And they degree, which I now understand that, you know, to pick up their early phrase, you can just do stuff, you can just try stuff and no one has all the answers. There are no like adults in the room. They're going to magically tell you exactly what to do um and you just kind of have to like IT a rate quickly and find your way that was like a big unlock in life from you understand there is a difference between being a high conviction just for the sake of IT and if you're wrong, you don't adapt and you don't try to be like truth seeking IT still is really not that effective.

The thing that we tried to do was really just believe whatever the results told us and really kind of try to go to do the thing in front of us. And there were a lot of things that we were high conviction and wrong on. But as soon as we realized we were wrong, we tried to like fully embracing conviction is great until the moment you have data one way or the other and they're a lot people hold on to .

pass the moment of data. So it's iterative. It's not just they're wrong and i'm right. You have to go show work.

but there is a long moment where you have to be willing to Operate without data. And at that point, you do after they just sort of run on conviction.

Yeah IT sounds like there's a focusing aspect. There are two like you had to make a choice and that choice had Better. You didn't have infinite choices. And so, you know, the prioritization itself wasn't exercise that made IT much more likely for you to succeed.

I wish I could go tell you like, oh, we knew exactly what was going to happen, and I was. We had this idea for language models from the beginning, and you know, we kind of went right to this. But obviously the story open the eyes that we did a lot of things that help us develop some scientific understanding, but we're not on the short path.

If we knew then what we know now, we could have speed on the whole thing to like an incredible degree doesn't work that way like you don't get to be right at every guess. And so we started off with a lot of assumptions both about the direction of technology but also what kind of company we were going to be and how we're going to be structured and how age I was going to go. And all of these things.

And we have been like humbled and badly wrong many, many, many times. And one of our strength is the ability to get punched in the face and get back up and keep going. This happens for scientific bets, for a, you know, being willing to be wrong about a bunch of other things we thought about how the world was going to work and what the sort of shape of the product was going to be.

Again, we had no idea, or I at least had no idea, maybe I grad ford did. I had no idea that language models are going to be the thing. You know, we started working on robots and agents, playing video games and all these other things. Then a few years later, GPT three happened. That was not so obvious at the time.

Yeah, that sounded like there was A A key insight around positive or negative sentiment around yet. G P, one.

even before GPT one. H, I think the paper was called the unsupervised sentiment. I think alex did IT alone, by the way, alex is this unlived outlier of human.

And so he did this incredible work, which was just looking at he he noticed there was one there on that was flip in positive and negative sentiment as IT was doing this generation amazon reviews, I think researchers might have typed up more, made a bigger deal, lot of other whatever. But, you know, is alex. So IT took people a while to, and fully internalized what a big deal that wasn't.

He then did GPT one, and somebody else killed that up in did GPT two. But IT was off of this insight that there was something, uh, amazing happening where at at the time and sugars landing, this is not really working. So he noticed this one really interesting property, which is there was another on that was flipping positive and negative with sentiment and yet that LED to the GPT series.

I guess one of the things that jack heller from case text, uh beard I think of him is maybe, I mean not surprisingly, A Y C alarm who got access to both three, three point five and four and he described getting four as sort of the big moment revelation because three point five would still do that. I would hu Cindy, more than he could use in a legal setting.

And then with four IT reached the point where if he chopped the prompts down small enough in the workflow, he could get IT to do exactly what what he wanted. And he built, you know, be huge test cases around IT and then sold that company for a six hundred fifty million dollars. So it's, you know, I think of like one of the first to commercialized GPT four in a relatively grand fashion.

I remember that conversation with him yeah with one beautiful like that was one of the few moments in that thing where I was aggregate. We have to be really great on our hands. Um when we first started trying to like sel GPT three to founder, they would be like it's cool.

It's doing something amazing is an incredible demo. But with the possible exception of copywriting, no great businesses were built on GPT and then three three point five came along and people starts like why he startups in particular started to do interest. I can no longer felt we are pushing a border appeal, like people actually wanted to buy the thing we were selling totally.

And then four, we kind of like got the like, just how many GPU can you give me? Oh yeah moment like very quickly after giving people access. So I I felt like, okay, we got something like really good on our hands.

So you knew actually from your users then totally like model dropped itself and you got your hands on IT. I was like, well, this this is Better.

We were totally impressed than to we had all of these like tests that we did on IT that were very you would look looked great and I could just do these things that we were all super impressed. Fy, also like when we all just playing around with IT and like getting samples back, was like, wow, it's like, I can do this now and they were, can ride and I can like, telefonica joke, slightly funny joke. And I can like, you know, do this and that.

And so IT felt really great. But, you know, you never really know if you have a hit product on your hands until you like put IT in customers hands yeah you're always too impressed with your own work yeah and and so we were all excited about that. This is really quite good. But until like the test happens, it's like the real test yeah yeah users yeah so there's some exciting until that until that moment happens. No.

I one of the switch gears a little bit so before you created obviously one of the brazza st A I labs ever to be created, um you started at nineteen at Y C. With the company called loops, which was basically find my friends geolocation you know probably what fifteen years before apple ended up making IT too .

early in any case yeah what .

drew you to that particular idea?

I was like interested in mobile phones, and I wanted to do something that got to like use mobile phones when like mobile was just started to like, know, still three years or two years before the iphone. But IT was clear that Carrying around computers in our pockets was somehow very big deal.

I mean, that's hard to believe now that there is a moment when phones were actually literally you just they .

were just a phone that I actually phone 你。

I mean, I try not to use that as an actual phone ever.

ever. I still remember the first phone I got that. And IT was this horrible like text base, mostly tax base. Brother IT was really slow. You could like you know do like you could so painfully socially check your email. Um but I was like A I don't know in high school sometimes high one I got a phone that could do that versus like just texting call and I was like hooked right then yeah I was like, all this is this is not a phone. This is like a computer we can Carry on or stuck with a dial pad for this .

excEllent history but this is me and I mean, now you have billions of people who they don't have a computer like to us growing up know that that actually was your first computer.

a yc ally like a like another copy of my first computer.

which is what a computer to us growing up. And the idea that you would Carry this little black mirror like kind of we've come a long way and considerable back then. So you know, even then you like technology and what was going to come with sort of in your brain?

Yeah, I was like a real I mean, i'm a real technology, but I always that was what I spent my friday .

nights came about. And then a one of the harder parts of IT was we didn't have the APP store. The iphone exist. Uh, you end up being a big part of that launch, I think a small part.

But yes, I used to be a little part of IT. IT was a great experience for me to have then through because I I kind of like understood what IT is like to go through a platform shift and how nessy the beginning is and how much like a little things you do can shape the direction that all goes. I was definitely other side of the then, like I was watching somebody else create the perform shift.

But IT was a super valuable experience to get to go through in sort of just see what. How IT happens? And how could these things change in how you would up through IT?

What was that experience like you ended up selling that company. And I was so probably the first time you were managing people and you know doing enterprise sales. All of these things were useful lessons from that first experience.

I mean, IT obviously was not a successful company. Um IT was and is a very painful thing to go through, but the rate of experience and education was incredible. Another thing that pg sar quoted somebody else saying, but always talk to me, as your twenties are always in apprentice, we don't know for what, and then you do your real work later.

And I did learn quite a lot, and i'm very grateful for IT. IT was like a difficult experience, and we never found product market fit really, and we also never like really found a way to get to scale e osi, which is just always hard to do. There is nothing that I that I have ever heard of that has a higher rate of generalize learning than doing to start up. So IT was great in essence here .

when you're one thousand nine and twenty, like riding the wave of some other platform shift to the shift from, you know, dumb cell phones to smartphones and mobile. And you know, here we are many years later, and your next act was actually, I mean, I got two x later, literally sporting one of the major platform old, yeah, but that's really what happening.

You know, eighteen, twenty year old are deciding that they could get their degree, but they're gonna miss the wave like all of the stuff. That's great. Everything's happening right now. What is do you have an intuitive sense like speaking to even a lot of the you know really great billion dollar company founders? Some of them are just not that aware of what's happening like the c it's wild.

yeah. I think that's why i'm so excited for start right now IT is because the world is still sleep in and all of this is such an astonishing degree now and then you have like the Y C. Founders being like, no, no, i'm unlike do the amazing .

thing and do IT very quickly yeah IT reminds me of one um facebook almost missed mobile so we're making web software and they're really good at IT. Yeah and like they all I mean they had to buy instagram like snapp chat and up what's up. So um it's interesting. The platform shift is always built by the people who are Young with no prior knowledge.

IT is I think it's great.

So there's this other aspect that's interesting in that I think you you know you and elon and BIOS and a bunch of people out there like they sort of start their journey as founders. You really, whether it's loops or zip two or really, really maybe your software like it's just a different thing that they start and then later they you know sort of get to level up. You know, is there a path that you recommend at this point if people are thinking, you know, I want to work on the crazy is hard test thing first. Should they just run towards that to the extent they can or is their value and you know, sort of solving the money problem first, being able to invest your own money like very deeply into the next thing?

It's a really interesting question that was definitely helpful that I could just like write the other cheek open eye and I think I would been hard to get somebody else to do that at the very beginning. Um and then elon didn't a lot at much higher scale and very grateful for and then other people that after that and and there's other things that i've invested in that i'm really happy to have been able to support.

And I don't, I think, going to be hard to get other people to to do IT. Um so that's great for sure. And I did, like we were talking about earlier, learn these extremely valuable lessons.

But I also feel like I kind of like was waste my time, for lack of a Better phrase, working on loop. I don't I definitely don't regret IT. It's like all part of the tapes story of life and I learned a ton .

in whatever else you have done differently or what would you tell yourself from like now to in a time time travel capture that would show up on your desk at stanford when you're looking well?

It's hard because A I was always the thing I most wanted to do and A I just like I want to school to study ai. But at the time I was working in the I love the one thing that I they told you was definitely don't work on. No, that works.

We try that. IT doesn't work. Thousand one time ago, I think I could have picked a much Better thing to work on the look. I don't know exactly what I would been, but IT all works satisfying. Yeah, there's this long history of people building more technology to help improve all the people's lives.

And I I actually think about this a lot like I think about the people made that computer and I ll know them um you know there are many of them probably long retired, but I am so grateful to them here. And some people worked super hard to make this thing at the limits of technology. I got a copy of that on my eighth birthday, and it's totally change my life now.

And the lives of love of the people too. They worked super hard. They never like, got to thank you for me, but I feel IT to them deeply and it's really nice to get to like add our brick to that long road of progress no um it's .

been great year for opening eye not without some drama yeah ah what did you learn from the universe of the house last fall? And how do you feel about some of the departures? I mean, teams do evolve, but how are you doing, man?

A terrible good. yeah. Uh, it's we kind of like speed run, uh, like medium size or even kind of like pretty big size to company arc.

They would want to take like a decade in two years. Accessibility is less than two years old. Yeah and there's like a lot of painful stuff that comes with that.

Um and there are you know any company as that scales goes through management teams some rate uh and you have to sort of the people who are really good at this year of one phase or not necessarily people that are good at the one to ten or the ten to one hundred face. We've also kind of like changed what we're gonna be a made plenty of mistakes along the way, done a few things really right. And that comes with a lot of change.

And I think the goal, the company, uh, the emerging A G I, whatever, how are you going to think about IT is like just keep making the best decisions we can at every stage. But IT does lead to a lot of change. I hope that we are heading towards a period now of more calm, but i'm sure there will be other periods in the future where things are very thin nby again.

So like how does OpenAI actually work right now, you know, and the quality and like th Epace t hat y ou're p ushing r ight n ow, I think, is like beyond world class compared to a lot of the other. You really establish software players like who came before.

This is the first time ever where I felt like we actually know what to do. Like I think from here too, ban agi will still take a huge amount of work. There are some known unknown, but I think we basically know what to go, what to go do.

And it'll take a while. It'll be hard. But that's tremendous, exciting. I also think on the product side, there's more to figure out.

But roughly, we know what to shoot out, what we want to optimize. That's a really exciting time. And when you have that clarity, I think you can go .

pretty now if you're going .

to say we're gona do these few things, we're going to try this very well. And our research path is fairly clear. Our infrastructure path is fairly clear.

Our product path is getting clear. You can orient around that super well. We for a long time did not have that. We were a true research lab.

And even when you know that, it's hard to act with the conviction on that because there's so many other good things you would like to do. But the degree to which you can get everybody aligned and point the same thing is a significant determinant. And how fast you can move.

I mean, IT sounds like we went from level one to level two very recently and that was really powerful and then we actually just had our one per fun. Um and then weirdly, one of the people who want I think they came in third, uh, was cancer. And so cat cam started up, you did I see recently, last year two.

And they were able to, during the hackers on build something that would iteratively improve an area foil from something that wouldn't fly to literally something that had. And there was also some a competitive amount of lift. And I mean, that sort of sounds like level four, which is, uh, you know the innovator stage.

It's very funny you say that I had been telling people for a while, I think that the level two to level three jump was going to happen, but then the level of three to level four jump was level two. Level three was going happen quickly, and then the level three to level four jump was somehow gonna much harder and require some medium sized or larger new ideas. And that demo in a few others have convinced me that you can get a huge amount of innovation just by using these current models and really creative. Well.

I mean, it's a what's interesting is basically camper already built sort of the underlying software for cat cam. And then your language is sort of the interface of the large language model that that which then can use the software like tool use. And then if you combine that with the idea of code gen, that's kind of a scary, crazy idea, right? Like not only can the a new large language model code, but IT can create tools for itself and then compose those tools similar to kind of thoughts with a one.

Yeah, I think things are gonna a lot faster than people appreciate you.

I know. Yeah, well, it's an exciting time to be alive, honestly.

You know, you mentioned early earth, that thing about discover all of physics. I was going to be a physicist that was, as far as to be a good one, had to, like, contribute the other way. The fact somebody else I really believe that is now i'm onna, go solve all the physics with the stuff like i'm so excited to be alive for that .

let's get a little four so .

happy for ever that person .

is yeah do you anna, talk about level three, four and five briefly?

Yes, so we realized that A G I had become this like a badly overloaded word, and people in all kinds of different things. And we tried to just say, okay, here's our best guess, roughly of the order of things. You have these level one systems with these chapattis. There be level two that would come, which should be these these reasoners we think we got there earlier this year um with the O N release three years agents uh ability to go off and do these longer term tasks uh you know maybe like multiple interactions with an environment asking people for help and they need IT working together. All of that I think we're going to get there faster than people expect if for as innovators like that's like a scientist and that's ability to go explore like a not well understood phenomena over like a long period of time and understand what's just kind of go just figure out out and then and in level five, this is the sort of slightly em office like do that. But at the scale of the whole company or no whole organization, whatever, that's gona be a pretty .

powerful thing. And he feels kind of fractals right, like even the things you have to do to get to two sort of round with level five and that you have multiple agents that then self correct that worked together. I mean, that kind of sounds like an organization to me, just like a very micro level.

Do you think that will have I mean, you famously talks about IT. I think jake talks about IT. It's like you will have companies that make you know billions of dollars per year and have like less than one hundred employees, maybe fifty, maybe twenty employees, maybe one IT doesn't seem like that.

I don't know what to make of that other than it's a great time to be a start of founder yeah but IT does feel like that's happening to me yeah um you know it's like one person plus ten .

thousand gp S I could happen to you and what advice you have for people watching who know either about to start or just started their start up.

Bet on this tech trend like bet on this trend is this is we are not in near the saturation point. The models are gonna so much Better so quickly. What you can do is to start founder with this versus what you can do without IT is so wildly different.

And the big companies, even the medium size companies, even the startups that are few years old, they're already unlike quarterly planning cycles. And google is on a year decade planning cycle to know how they even do that anymore. But your advantage with speed and focus on conviction and the ability to react to how far the technology is moving, that is that is the number one edge of the start up kind of ever, but especially right now.

So I would definitely like build something with a eye, and I would definitely like take advantage of the ability to see a new thing and build something that day, rather than like put IT into a cordial plan cycle. I guess the other thing I would say is IT is easy when there's a new technology platform to say, well, because i'm doing something, the A I, the the rule, the laws of business don't apoyo Y I have this magic technology and so I don't have to build uh a mode or a um you know competitive edges Better product because you i'm doing A I you're not so that I need and that's obviously not true. But what you can get out this short term explosions of growth by embracing new technology more quick than somebody else and remembering not to fall for that, and then you stop to build something of enduring value. That's b everyone can build .

an absolutely incredible demo right now, but everyone can build an incredible demo. But building a business, then that's the restaurant. The rules still apply.

You can do IT faster than ever before and Better than ever before.

but you have to build a business. What are you excited about in twenty twenty five?

What's to come? E G, I yeah excited for that. Uh, what am I excited for? Um, we're in a kid. I'm more excited for that.

The great lakes have been incredible. Yeah probably that that's that's going .

to be really like most .

excited forever in life. Yeah IT changes your life completely so I can IT. Well, here's the building that Better world for you know, our kids and really.

hopefully the whole world.

This is a lot of fun. Thanks for having out sand. Thank you.