How To Build The Future: Sam Altman

we said from the very beginning we were going to go after AGI 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 resourced than Deep Mind and others and so we said okay they're going to try a lot of things and we've just got to pick one and really concentrate and that's how we can we can win here most of the world still does

not understand the value of like a fairly extreme level of conviction on one bet that's why I'm so excited for startups right now it is because the world is still sleeping on all this to such an astonishing degree we have a real treat for you today Sam Alman thanks for joining us 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 to think about that something like that that's wild I'm glad it's being rebooted that's right let's

talk about your newest essay on uh the age of intelligence you know is this the best time ever to be starting a technology company let's at least say it's the best time yet hopefully there'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 could before and I would expect the companies to be more amazing and impactful in everything else so yeah I think it's the best time yet big companies have the edge when things are like moving slowly and not

that Dynamic and then when something like this or mobile or the internet or semiconductor Revolution happens or probably like back in the days of the Industrial Revolution that was when upstarts had their have their Edge so yeah this is like and it's been a while since we've had one of these so this is like pretty exciting in the essay you actually say a really big thing which is ASI super intelligence is actually thousands of days away maybe I mean that's our hope our guess whatever uh but that's a very wild statement yeah um tell us

about it I mean that's that's big that is really big I can see a path where the work we are doing just keeps compounding and the rate of progress we've made over the last three years continuous for the next three or six or nine or whatever um you know nine years would be like 3500 days or whatever if we can keep this rate of improvement or even increase it that system will be quite capable of doing a lot of things I think already uh even a system like A1 is capable of doing like quite a

lot of things from just like a raw cognitive IQ on a closed end well- defined task in a certain area I'm like oh one is like a very smart thing and I think we're nowhere near the limit of progress I mean that was an architecture shift that sort of unlocked yeah a lot and what I'm sort of hearing is that these things are going to compound we could hit some like unexpected Ed wall or we could be missing something but it looks to us like there's a lot of compounding in front of us still to

happen I mean this essay is probably the most techno Optimist of almost anything I've seen out there some of the things we get to look forward to uh fixing the climate establishing a space Colony the discovery of all of physics uh near Limitless intelligence and abundant energy I do think all of those things and probably a lot more we can't even imagine are maybe not that far away and one of I I think it's like tremendously exciting that we can talk about this even semi-seriously now one of the things that I always have loved the

most about YC is it encourages slightly implausible degrees of techno 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 this is not going to work you can't do this thing you can't do that I think the kind of early PG Spirit of just encouraging Founders to like think a little bit bigger is like it is a special thing in the world the Abundant energy thing seems like a pretty big deal you know there's sort of path

a and path B you know if we do achieve abundant energy seems like this is a real unlock almost any work not just you know knowledge work but actually like real physical work yeah could be unlocked with ro Robotics and with language and Intelligence on tap like there's a real age of abundance I think these are like 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 unlock that would happen if we could just get truly abundant intelligence truly abundant

energy what we'd 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'd be nice to be able to run lots of AI and that takes energy too uh I think that would be a huge unlock and the fact that it's I'm not sure to be whether like whether it be surprised that it's all happening the same time or if this is just like the natural effect of an increasing rate of

technological progress but it's certainly very exciting time to be alive and great time to do a startup well so we sort of walk through this age of abundance you know maybe you robots can actually manufacture 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 breakthrough

we would be like okayish 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 we'll solve every problem in physics so we're going to figure this out it's just a question of when and we deserve it uh there's you know someday we'll be talking not about Fusion or whatever but about the dys feere and that'll be awesome too yeah this is a point in time whatever feels like abundant energy to us will feel like not nearly enough

to our great-grandchildren and there's a big universe out there with a lot of matter yeah wanted to switch gears a little bit to sort of your earlier you were mentioning uh Paul Graham who brought us all together really created why combinator he likes to tell the story of how you know how you got into YC was actually you were a Stanford freshman um and he said you know what this is the very first YY batch in 2005 and he said you know what you're a freshman and wey will still be here uh next time you

should just wait and you said I'm a sophomore and I'm coming and widely known in our community as you know one of the most formidable people where do you think that came from that one story I think I I I would happy i' be happy if that like drifted off hisory well now it's it's purely immortalized here here it is my memory of that is that like I needed to reschedule an interview one day or something um and PG tried to like say like I just do it next year or whatever and then I think

I said some nicer version of I'm a sophomore and I'm coming but yeah you know these things get slightly apocryphal it's funny I don't and I say this with 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'm 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 going to like do this thing that from first principles seems like fine and I always felt

a little bit weird about that and then I I remember one of the things I thought was so great about YC and still that I care so much about YC 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 does resonate as a like accurate self-identity thing is I do think you can just do stuff or try stuff a surprising amount of the time and I think more of that is a good thing and then I think one of

the things that both of us found at YC was a bunch of people who all believed that you could just do stuff for a long time when I was trying to like figure out what made ycu so special I thought that it 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 special and inspiring and 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 pieces of advice I would give to young people now is finding that peer group as early as you can was so important to me um and I didn't realize it was something that mattered I kind of thought ah like I have you know I'll figure it out on my own but man being around like inspiring peers so so valuable what's funny is both of us did spend time at Stanford I actually did graduate which is I probably shouldn't have done that but I did sford it's great you pursued

the path of uh you know far greater return uh by dropping out but you know that was a community that purportedly had a lot of these characteristics but I was still Beyond surprised at how much more potent it was with a room full of Founders it was I was just going to say the same thing actually I liked Samford a lot yeah but I was 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 did the thing you were competing with

your peers on was like who was going to get the internship at which Investment Bank which I'm embarrassed to say I fell on that trap this is like how powerful peer groups are um it was a very easy decision to not go back to school after like seeing what the like YC Vibe was like yeah uh there's a powerful quote by uh 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 it will tell you it 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 takeaways at least for myself is you no one is immune to peer pressure and so all you can do is like pick good peers yeah obviously you know you went on to create looped you know sell that go to Green Dot and then we ended up getting to work together at YC talk to me about like the early days of YC research like one of the really cool things that

you brought to YC was this experimentation and and you sort of I mean I 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 laran Sur gaze of the world and that you know AI was some sort of at the tip of everyone's tongue because it felt so close and yet it was you know that was 10 years ago the thing I always thought would be the coolest retirement job was to get to like run a research lab and it was

not specifically to AI at that time when we started talking about YC research well not only was it going to it it did end up funding like a bunch of different efforts and I wish I could tell the story of like oh was obvious that AI was going to work and be the thing but like we tried a lot of bad things too it around that time I read a few books on like the history of zerox Park and Bell labs and stuff and I think there were a lot of people like it was in

the air of Silicon Valley at the time that we need to like have good research Labs again and I just thought it would be so cool to do and it was sort of similar to what YC does and that you're going to like allocate Capital to smart people and sometimes it's going to work and sometimes it's not going to and I just wanted to try it AI for sure was having a mini moment this was like kind of late 2014 2015 early 2016 was like the super intelligence discussion like the book super intelligence was happening

Bo yep yeah the Deep Mind had a few like impressive results but a little bit of a different direction you know I had been an AI nerd forever so I was like oh it' be so cool to try to do something but it's very hard to say was imet out yet imag net was out yeah yeah for a while at that point so you could tell if it was a hot dog or not you could sometimes yeah that was getting there yeah you know how did you identify the initial people you wanted involved in you

know YC research and open AI I mean Greg Greg Brockman was early in retrospect it feels like this movie montage and there were like all of these like you know at the beginning of like the Bai movie when you're like driving around to find the people and whatever and and they're like you son of a I'm in right right like Ilia I like heard he was really smart and then I watched some video of his and he's ALS now he's extremely smart like true true genuine genius 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 him and he didn't respond so I just like went to some con conference he was speaking at and we met up and then after that we started talking a bunch and and then like Greg I had known a little bit from the early stripe days what was that conversation like though it's like I really like what your your ideas about Ai 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 were going to go after AGI at a time when in the FI you weren't allowed to say that because that just seemed possibly crazy and you know borderline irresponsible to talk so that got his attention immediately it got all of the good young people's attention and the derion derision whatever that word is of the mediocre 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 I guess I was 30 then and so you had like these people who were like those are these irresponsible 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 are the same kind of people who would have said like it's a you know I'm a sophomore and I'm coming or whatever and 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 it kind of came together over the course of in fits and starts but over the course of like nine months and then it started h i mean and then it started it started happening and one of my favorite like memories of all of open eye was Ilia had some reason that with Google or something that we couldn't start in we announced in December of 2015 but we couldn't start until January of 2016 so like January 3rd something like

that of 2016 like very early in the Month people come back from the holidays and we go to Greg's apartment maybe there's 10 of us something like that and we sit around and it felt like we had done this Monumental thing to get it started and everyone's like so what do we do now and what a great moment it reminded me of when startup Founders work really hard to like raise a round and they think like oh I accomplished this great we did it and then you sit down and say like now we got to

like figure out what we're going to do it's not time for popping champagne that was actually the starting gun and now we got to run yeah and you have no idea how hard the race is going to be it took us a long time to figure out what we're going to do um but one of the things I'm really amazingly impressed by Ilia in particular but really all of the early people about is although it took a lot of twist and 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 flip charts or whiteboards I don't remember which in Greg's apartment and then we went off and you know did some other things that worked or didn't work or whatever some of them did and eventually now we have this like system and it feels very crazy and very improbable looking backwards that we went from there to here with so many detours on the way but got where we were pointing was deep learning even on that flip chart initially yeah uh I mean more specifically than

that like do a big unsupervised model and then solve RL was on that flip chart one of the flip charts from a very this is before Greg's apartment but from a very early offsite I think this is right I believe there were three goals for the for the effort at the time it was like figure out how to do unsupervised learning solve RL and never get more than 120 people missed on the third one but right the like d the predictive direction of the first two is pretty good so deep learning then the second big

one sounded like scaling like the idea that you could scale that was another heretical idea that people actually found even offensive you know I remember a rash 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 heretical beliefs at the time we didn't know how predictably better a got with scale that didn't come for a few years later it was a hunch first and then you got the data to show how predictable it was

but but people already knew that if you made these neural networks bigger they got better yeah um like that was we were sure of that um before we started and what took the like where that keeps coming to mind is like religious level of belief was that that wasn't going to stop everybody had some reason of oh it's not really learning it's not really reasoning I can't really do this it's you know it's like a parlor 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 or bad thing to say it was that there's got to you you know this is like you're going to perpetuate an AI winter you're going to 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 got the scaling results it just kind of breaks my intuition even now and at some point you have to just look at the scaling loss and say we're going to keep doing this and this is

what we think it'll do and it also it was starting to feel at that time like something about learning was just this emergent phenomenon that was really important and even if we didn't understand all of the details in practice here which obviously we didn't and still don't that there was something really fundamental going on it was the PG ISM for this is we had like discovered a new Square in the periodic table yeah and so it we just we really wanted to push on that and we were far less resourced than Deep Mind and others

and so we said okay they're going to try a lot of things and we've just got to pick one and really concentrate and that's how we can we can win here which is totally the right startup takeaway and so we said well we don't know what we don't know we do know this one thing works so we're going to really concentrate on that and I think some of the other efforts were trying to outsmart themselves in too many ways and we just said we'll just we'll do the thing in front of us and keep pushing

on it scale is this thing that I've always been interested in um at kind of just the emergent properties of scale for everything for startups turns out for deep learning models for a lot of other things I think it's a very underappreciated property and thing to go after and I think it's you know when in doubt if you have something that seems like it's getting better with scale I think you should scale it up I think people want things to be uh you know 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 that well understood about open AI is 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 smartest people in the world you can push on something really hard yeah and they're motivated Andor 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 embedded in some of the criticism from maybe the Elders of the industry at the moment was sort of that you know know you're going to waste a lot of resources and somehow that's going to result in an AI winter like people won't give resources anymore it's funny people were never sure if we were going to waste resources or if we were doing something kind of vaguely immoral by putting in too much resources and you were supposed to spread it 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 bet and so we said okay we have this evidence we believe in this we're going to at a time when like the normal thing was we're going to spread against this bet and that bet and that bet definite Optimist you're a definite Optimist and I think across like many of the successful YC startups you see a version of that again and again yeah that sounds right when the world gives you sort of push back and the push

back doesn't make sense to you you should do it anyway totally one of the 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 YC I I really had this deep belief that somewhere in the world there were adults in charge adults in the room and they knew what was going on and someone had all the answers and you know if someone was pushing back on you they probably knew what was going on and

the degree to which I Now understand that you know to pick up the earlier phrase you can just do stuff you can just try stuff no one has all the answers there are no like adults in the room that are going to magically tell you exactly what to do um and you just kind of have to like iterate quickly and find your way that was like a big unlock in life for me to understand there is a difference between being uh High conviction just for the sake of it and if you're wrong and 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 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 embrace it conviction is great until the moment you have data one way or the other and there are a lot of people who

hold on it past the moment of data so it's it's iterative it's not just they're wrong and I'm right you have to go show your work but there is a long moment where you have to be willing to operate without data and at that point you do have to just sort of run on conviction yeah it sounds like there's a focusing aspect there too like you had to make a choice and that choice had better you know you didn't have infinite choices and so you know the prioritization itself was an 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 it was you know we had this idea for language models from the beginning and you know we kind of went right to this but obviously the story of opening eyes that we did a lot of things that helped us develop some scientific understanding but we're not on the short path if we knew then what we know now we could have speedrun this 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 were going to be structured and how AGI 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 strengths is the ability to get punched in the face and get back up and keep going this happens for scientific bets for uh 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 Alec Radford did I had no idea that language models were going to be the thing um you know we started working on robots and agents PL video games and all these other things then a few years later gbd3 happened that was not so obvious at the time yeah it sounded like

there was a a key Insight around positive or negative sentiment around n GT1 even before gpt1 Oh before he I think the paper was called the unsupervised sentiment on and I think Alec did it alone by the way Alec is this unbelievable outlier of a human and so he did this incredible work which was just looking at he he noticed there was one neuron that was flipping positive or negative sentiment as it was doing these generative Amazon reviews I think other researchers might have hyped it up more made a bigger deal out of it or

whatever but you know it was Alex so it took people a while to I think fully internalize what a big deal it was and he then did gpt1 and somebody else scaled it up into gpt2 um but it was off of this Insight that there was something uh amazing happening where and at at the time unsupervised learning was just not really working so he noticed this one really interesting property which is there was a neuron that was flipping positive or negative with sentiment and yeah that led to the GPT series I guess one of the

things that Jake heler from case text uh we I think of him as maybe I mean not surprisingly a YC Alum who got access to both uh 3 3.5 and four and he described getting four as sort of the big moment Revelation because 3.5 would still do yeah I mean it would hallucinate 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 into workflow he could get it to do exactly what what he wanted and he built you know huge

test cases around it and then sold that company for $650 million so it's uh you know I think of him as like one of the first to commercialize gp4 in a relatively Grand fashion I remember that conversation with him yeah with one gp4 like that was one of the few moments in that thing where I was like okay we have something really great on our hands um when we first started trying to like sell gpt3 to found Founders they would be like it's cool it's doing something amazing it's an incredible demo but with the possible

exception of copyrighting no great businesses were built on gpt3 and then 3 3.5 came along and people startups like YC startups in particular started to do interest like it no longer felt like we were pushing a boulder uphill so 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 gpus can you give me oh yeah moment like very quickly after giving people access so we felt like okay we got something like really good on our hands so you you knew actually

from your users that totally like when the when the uh model dropped itself and you got your hands on it it was like well this this is better we were totally impressed then too we had all of these like tests that we did on it that were very it like looked great and it could just do these things that we were all super impressed by also like when we were all just playing around with it and like getting samples back I was like wow it's like it can do this now and they were it can

rhyme and it can like tell a funny joke slightly funny joke and it 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 customer hands yeah you're always too impressed with your own work yeah and and so we were all excited about it we were like oh this is really quite good but until like the test happens it's like the real test is yeah the real test is users yeah so

there's some anxiety until that until that moment happens yeah I wanted to switch gears a little bit so before you created obviously one of the craziest AI Labs ever to be created um you started at 19 at YC with a company called looped which was uh basically find my friend's geolocation you know probably what 15 years before Apple ended up making it too early in any case yeah 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 phone this

was when like mobile was just starting was like you know still 3 years or years before the iPhone but it was clear that carrying around computers in our pockets was somehow a very big deal I mean that's hard to believe now that there was a moment when phones were actually literally you just they were just a phone they were an actual phone yeah yeah I mean I try not to use it as an actual phone ever really I still remember the first phone I got that had internet on it and it was this horrible like

text based mostly text-based browser it was really slow you could like you know do like you could so painfully and so slowly check your email um but I was like a I don't know in high school sometime in high school and I got a phone that could do that versus like just text and call and I was like hooked right then yeah I was like ah this is this is not a phone this is like a computer we can carry and we're stuck with a dial pad for this accident of history but this is going

to be awesome and I mean now you have billions of people who they don't have a computer like to us growing up you know that that actually uh was your first computer not physically is a replica or like another copy of my first computer which is lc2 yeah so this is what a computer was to us growing up and the idea that you would carry this little black mirror like kind of we've come a long way unconscionable back then yeah so you know even then you like technology and what was going to come was sort

of in your brain yeah I was like a real I mean I still am a real tech nerd but I always that was what I spent my Friday nights thinking about and then uh one of the harder parts of it was we didn't have the App Store the iPhone didn't exist uh you ended up being a big part of that launch I think a small part but yes we dig it to be a little part of it it was a great experience for me to have been through because I I kind of like understood what

it is like to go through a platform shift and how messy the beginning is and how much like little things you do can shape the direction it all goes I I was definitely on the other side of it then like I was watching somebody else create the platform shift but it was a super valuable experience to get to go through and sort of just see what how it happens and how quickly things change and how you adapt through it what was that experience like you ended up selling that company uh was 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 su ful company um it was and so it's a very painful thing to go through but the rate of experience and education was incredible another thing that PG said or quoted somebody else saying but always stuck with me is your 20s are always an apprenticeship but you 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 escape velocity which is just always hard to do there is nothing that I that I have ever heard of that has a higher rate of generalized learning than doing a startup so it was great in that sense you know when you're 19 and 20 like riding the wave of some other platform shift this 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 you know I mean I guess two acts later literally spawning one of the major platform sh we all get old yeah but that's really what's happening you know uh 18 20 year olds are deciding that they could get their degree but they're going to miss the wave like cuz all of the stuff that's great everything's happening right now like proud do you have an intuitive sense like speaking to even a lot of the you know really great billion dooll company Founders some of them are just

not that aware of what's Happening like there're C to it's wild I think that's why I'm so excited for startups right now is because the world is still sleeping on all of this to such an astonishing degree yeah and then you have like the YC Founders being like no no I'm going to like do this amazing thing and do it very quickly yeah it reminds me of when um Facebook almost missed mobile because they were making web software and they were really good at it yeah and um like they they I mean they had to

buy Instagram like Snapchat right up yeah and WhatsApp so um it's interesting the platform shift is always built by the people who are young with no prior knowledge it's it is I think it's great so there's this other aspect that's interesting in that I think you're you know you and Elon and uh Bezos and a bunch of people out there like they sort of start their Journey as Founders you know really you know whether it's looped or zip to or you know really in maybe pure soft 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 craziest hard tech thing first should they just run towards that to the extent they can or is there value in 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 it was definitely helpful that I could just like write the early checks for

open Ai and I think it would have been hard to get somebody else to do that at the very beginning um and then Elon did it a lot at much higher scale which I'm very grateful for and then other people did 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 it would have been 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 wasting my time for lack of a better phrase working on looped I don't I definitely don't regret it it's like all part of the tapestry of life and I learned a ton and whatever else what would you have done differently or what would you tell yourself from like now to in a Time cap in like time travel capsule that would show up on your desk at Stanford when you were 19 well it's hard because AI was always the thing I most wanted to do

and AI just like I went to school to study AI but at the time I was working in the AI lab the one thing that I they told you is definitely don't work on neural networks we tried that it doesn't work a long time ago I think I could have picked a much better thing to work on than loped I don't know exactly what it would have been but it all works out it's fine yeah there's this long history of people building more technology to help improve other people's lives and I I actually think about

this a lot like I think about the people that made that computer and I don't know them um you know they're many of them probably long retired but I am so grateful to them yeah and some people worked super hard to make this thing at the limits of technology I got a copy of that on my eth birthday and it totally changed my life yeah and the lives of a lot of other people too they worked super hard they never like got to thank you for me but I feel it to them very deeply and

it's really nice to get to like add our brick to that long road of progress yeah um is it's been a great year for open AI not without some drama uh always yeah we're good at that uh what did you learn from you know sort of the ouer last fall and how do you feel about some of the you know departures I mean teams do evolve but how are you doing man tire but good yeah uh it's we've kind of like speedrun uh like medium siiz or even kind of like pretty big siiz tech company

Arc that would normally take like a decade and two years like chpt is less than two years old yeah and and there's like a lot of painful stuff that comes with that um and there are you know any company as it scales goes through management teams at some rate uh and you have to sort of the people who are really good at the zero to one phase are not necessarily people that are good at the 1 to 10 or the 10 to the 100 phase we've also kind of like changed what were going to be

um 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 of the company uh the emerging AGI or whatever however you want 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 Dynamic again so I guess how does

open AI actually work right now you know I mean the quality and like the pace that you're pushing right now I think is like Beyond world class compared to a lot of the other you know really established 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 to building an AGI will still take a huge amount of work there are some known unknowns 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 tremendously exciting I also think on the product side there's more to figure out but roughly we know what to shoot at and what we want to optimize for that's a really exciting time and when you have that Clarity I think you can go pretty fast yeah if you're willing to say we're going to do these few things we're going to try to do them very well and our research path is fairly clear our infrastructure path is fairly clear our product path is getting clearer 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 it because there's so many other good things You' like to do yeah but the degree to which you can get everybody aligned and pointed at the same thing is a significant determinant in how fast you can move I mean sounds like we went from level one to level two very recently and that was really powerful um and then we actually just had our 01 hackathon at YC

that was so impressive that was super fun um and then weirdly one of the people who won I think they came in third uh was camper and so CAD cam startup you know did YC recently last year or two and uh they were able to during the hackathon build something that would iteratively improve an air foil from something that wouldn't fly to literally something that had yeah that was awesome 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 I had been telling people for a while I thought that the level two to level three jump was going to happen but then the level three to level four jump was level two to level three was going to happen quickly and then the level three to level four jump was somehow going to be much harder and require some medium-sized or larger new ideas and that demo and a few others have convinced me that you can get a huge amount of innovation just by using these current models in really creative ways well yeah

I mean it's uh what's interesting is basically camper already built sort of the um underlying software for CAD Cam and then you know language is sort of the interface to the large language model that then 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 uh you large language model code but it can create tools for itself and then compose those tools similar to you know chain of thoughts with o1 yeah I

think things are going to go a lot faster than people are appreciating right now yeah well it's a an exciting time to be alive honestly you know we you mentioned earlier that thing about discover all of physics I uh I was want to be a physicist wasn't smart enough to be a good one had to like contribute in this other way but the fact that somebody else I really believe is now going to go solve all the physics with the stuff like I'm so excited to be alive for that let's get to level four so

happy for whoever that person is yeah do you want to talk about level three four and five briefly yeah so we realized that AGI had become this like badly overloaded word and people meant 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 which are these chat Bots there'd be level two that would come which would be these this these reasoners we think we got there earlier this year um with the o1 release three is Agents U ability

to go off and do these longer term tasks uh you know maybe like multiple interactions with an environment asking people for help when they need it working together all of that and I I think we're going to get there faster than people expect for as innovators like that's like a scientist and you know 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 it out and then and then level five this is the sort of slightly amorphous like do

that but at the scale of the whole company or you know a whole organization or whatever ever that's going to be a pretty powerful thing yeah and it feels kind of fractal right like even the things you had to do to get to two sort of rhyme with level five and that you have multiple agents that then self-correct that work together I mean that kind of sounds like an organization to me just at like a very micro level do you think that we'll have I mean you famously talked 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 100 employees maybe 50 maybe 20 employees maybe one it does seem like that I don't know what to make of that other than it's a great time to be a startup founder yeah but it does feel like that's happening to me yeah um you know it's like one person plus 10,000 gpus pretty pretty powerful Sam what advice do you have for people watching who you know either about to start or just started their startup bet

on this Tech trend bet on this trend it's this is we are not near the saturation point the models are going to get so much better so quickly what you can do as a startup founder with this versus what you could do without it is so wildly different and the big companies even the mediumsized companies even the startups that are a few years old they're already unlike quarterly planning cycles and Google is on a year decade planning cycle I don't know how they even do it anymore but your advantage with speed and focus and conviction

and the ability to react to to how fast the technology is moving that is that is the number one edge of a startup kind of ever but especially right now so I would definitely like build something with AI 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 quarterly planning 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 with AI the the rule

the laws of business don't apply to me I have this magic technology and so I don't have to build uh a moe or a um you know Competitive Edge or a better product it's because you know I'm doing Ai and you're not so that's all I need and that's obviously not true but what you can get are these short-term explosions of growth by embracing a new technology more quickly than somebody else and remembering not to fall for that and that you still have to build something up been value that's I think that's a good thing

to keep in mind too yeah everyone can build an absolutely incredible demo right now but everyone can build an incredible demo but building a business man that's the brass ring the rules still apply you can do it faster than ever before and better than ever before but you still have to build a business what are you excited about in 2025 what's to come AGI yeah uh excited for that uh what am I excited for um we a kid I'm more excited for that than congratulations ever been incredible yeah probably that that's going to be that's

the thing I've like most excited for ever in life yeah it uh changes your life completely so I cannot wait well here's to building that better world for you know our kids and really hopefully the whole world this is a lot of fun thanks for hanging out Sam thank you [Music]