there are two strategies to build on AI right now there's one strategy which is assume the model is not going to get better and then you kind of like build all these little things on top of it there's another strategy which is build assuming that open air is going to stay on the same rate of trajectory and the models are going to keep getting better at the same Pace it would seem to me that 95% of the world should be betting on the latter category but a lot of the startups have been built in the former category when we just do our fundamental job because we like have a mission we're going to steamroll you ready to go [Music] ~ Preview Segment Removed ~ guys I'm so excited for this I've wanted to do this for a long time also this is the first time that you've done an interview together I think it is yeah that's right this is going to be the most unique interview then that you've done together so this is very exciting I want to start I spoke to many mutual friends before and they said we've got to start with context Sam what gave you the conviction to to do this 7 years ago I think they were two things that seemed well I've been interested in AI since I was a little kid um but and I studied at College nothing was working but when we started there were two things that seemed really important one deep learning seemed to actually legitimately be working and two it got better with scale we didn't know how predictively it got better with scale at the time but it was clearly that like bigger was better and that seemed like a remarkable set of things and the confusing thing to us at the time was like why does everybody else not see this and why is everybody else not jumping on it but they weren't and so we wanted to do it can I ask when there were those moments of Doubt from everyone else which there were across those years what gave you the conviction to stick at it when bluntly very few others had that same confidence it just seemed to us like it was going to work and we kept making progress like we it was not it was I wouldn't call I would not call it Blind Faith although there is some amount if you just you know you got to believe you can do a hard thing but it it felt really important to us to do this that if we could do it it would be you know hugely meaningful um to the world in some way and that it might work like we had an attack Vector we believed in we had uh and then we had continued data that the approach was working of course the specifics took a long time to figure out uh you know we did not start off doing language models obviously we kind of knew that if we could keep doing things that we previously thought were impossible that was somehow a good sign for progress and we had this like fundamental conviction on the approach and the attack Vector at a very high level for a very long time and the details took a long time to work out and many brilliant discoveries by our colleagues there was never any doubt that AI would be a big deal if we could do it so that's helpful like it's it's going to be really valuable um the approach we got successively more confident in although it did take some wandering in the jungle for a while or the desert whatever that phrase is um and then you know it's like if you believe something with high conviction and everybody else doubts it it's like slightly motivating yeah it's definitely kind of annoying but it's slightly motivating I mean there a VC that would be contrarian which is not what we do cuz we're sheep but I I do want to start on on actually the relationship that we have here because it is such a unique partnership and again we said this is the first time you've been interviewed together how did the partnership come to be braad why didn't you tell me that sure well Sam and I worked together a long time um and and we actually we spent a lot of time at YC looking at um this batch of companies that was starting to hit the growth stage that were these really deeply technical projects nuclear fusion reactors quantum computers self-driving cars satellites things like that and I was kind of focused on those uh on those those companies um from an investment perspective and open ey was kind of the first company I saw that I was like you know what like this one's kind of unique because it kind of just seems to be getting better over time it's not this kind of binary risk um and I remember pointing that out to Sam and saying I think there's something that's going to be different about this company as compared to some of the other companies that we were looking at at the time um and I ended up spending more time with Greg and Ilia um and uh the properties that Sam describes of these systems just getting better with scale at first kind of unpredictably and then more predictably I thought that was just so unique and um and I think we kind of saw the same thing maybe somewhat from different angles uh I saw it mostly from an investment perspective of if that's true this is going to be be really important um just as an investment outcome just as something that's going to have real impact on the world um and so I really felt that kind of conviction early on and I just wanted to help anyway I could did you have that plan that you wanted to join fulltime like when did that come into fruition that you wanted this to be your mission for the next multi- deade it it wasn't at first I actually was mostly just trying to help Sam recruit a CFO Brad actually worked at open a full time before I did that's true I beat him there um first time I've beaten Sam on anything but uh just take it as a win yeah um but no I was trying to to help him recruit and at the time no one wanted the job um I asked probably 25 people uh if they would want to be CFO of open AI which at the time was just a a small kind of non sleepy nonprofit and I went over for 25 and honest to God the reason I'm here is because I was so embarrassed to come back over 25 that I said you know what why don't I just help out uh nights and weekends and uh and that that turned into fulltime very quickly so I had no idea about that yeah I was sort of doing like half my time on opening on YC wow yeah and there were like all kinds of you get fulltime YC then some uh I started doing open a full it was kind of like a gradual is process but I think like by the spring or summer of 2019 okay so so Brad beat you to open AI I I think that great Partnerships are about complimentary skill sets that's for sure and so I wanted to hear from each of you like an All-Star Mr and Ms like what is Brad amazing at that the world doesn't know look I think one of the one sign of like a good partnership I'm thankful to have this with like a lot of the key people at open AI certainly with Brad is like um if you can't do each other's job you maybe Brad could do my job for a week I certainly could not do Brad's job for a week um and I I think that ability to divide up as a team um and have a very high bandwidth Communication channel with each person and all together as a leadership team is super important Brad is good at a lot of things uh I'll talk about just two here in the interest of time one is adaptability uh Brad joined to do Finance obviously and now does something I guess it's like in the sphere of Finance but very very different um we didn't have a business at all or we didn't have an appreciable business until very recently and when it became clear that we were going to have a very fast growing business um kind of like looks around was like really need somebody we got to we got to get someone to do this and uh I kind of like looked around the room and I asked Brad to do it and it was and he was just like okay I'll figure it out like I'll you know uh just like you know I might need like a little bit of time to get up to speed but this is you know I've done like business sish stuff before and can go like build all this out so the the willingness to just like take on new challenges at each level of company scale and figure it out as you're going Brad is super great at and then the other one is um well I'm like financially literate so all of that seems amazing to me but but but to build out a new product category and go to market function around that takes a very wide array of skills and a great deal of patience um and sort of uh like a customer Obsession uh from a product to a business model to a how we're going to deal with customer support and everything else that goes around that um and Brad's ability to see the whole picture of that and how it comes together so that you know a company that we're here today at this Enterprise Sales Event I think if you had said a year ago we're going to be like a great organization well not yet a great organization we're going to even be a very good organization at doing uh you know an Enterprise go to market function I would have said uh very low chance that that's going to happen and now we have a pretty good one I mean we're going to discuss it later cuz I think the Market that You' built is incredible um if we flip the tables though what would you say is Sam's biggest strength that not many people consider or no well I some people know this but I think you can say none that's fine um I'll I'll say two things uh they're interrelated one is I think at any given point in a company's life there's only like one to three things that really matter at that point those things change but there there's almost never 10 things that really matter and I think Sam has an incredible ability to be laser focused on those one to three things and that spills over into how we run the team uh because if I know what he's focused on and we may disagree on what those things are oftentimes I think we agree but um if we can at least align on what those things are and they may not be the right Global bets but they are the ones that feel the right right at the time then it helps me to translate down to the teams that I'm building on you know whether it's to that we want to be um you know more Enterprise focused or it's that we want to really actually um change the bet we're making on Research or we actually want to bet more on One Thing versus another um or we really need to get this thing right it helps to keep us moving very fast um and I think that's kind of the key to uh to how to to kind of maintain um velocity at scale that most companies start to lose inherently is the number of things and what the perceived number of important things are goes up um and the second thing I'll say is just a long like a very like long-term future orientation um and you kind of have this like idea that you're running at this thing that's like really far out there um and you're the the process of justifying what those one to three things are by the way that's most important is really just a function of trying to figure out uh what the one to three things are that are the fastest accelerants to get us to that point um and Sam's has this like maniacal focus on that future World um my job is just to to fill in everything in between what are the one or two things that you think are most important to you now then there are a lot of AI orgs in the world that can um copy what other people do uh like once you know something that's possible once you kind of know the r shape of it once you know that people want it that's not so hard um or it's like somewhat hard it's really hard to figure out how to do something new for the first time and to do that consistently uh over years and hopefully for lucky enough over decades building an research org and a product org and a whole company that puts these things out in the world cuz we also innovate on business models and anything else this culture of repeated Innovation so that we're not just making GPT 5 amazingly great but six seven 8 whatever we're going to call those we won't keep numbering them like that at that point um making sure that we're set up to do that uh from a thinking about where the researches can take us what that means for where the products got to go what that means for where the whole company has to follow um that's a big one what are the biggest things that would prevent or slow down the velocity of open AI decision making Innovation I think we have the best researchers and best research culture that I'm aware of in the world um if we lost either of those things that would be really bad not having enough compute resources would be uh really bad and I think you know we we love doing cool research cuz scientific advancement is like the coolest most exciting thing in the world but really we're here to like do useful stuff for other people and if we do the best research in the world and then we make it as efficient as we can but we still don't have enough compute to provide it to everybody on Earth who's wants to use it and is going to want to use it so much more as these models get way better that would get in the way that'd be really bad so uh the second thing I was going to say for priorities uh is think about how we get enough compute to fulfill the demand of people who want to use these how do you think about answering that I know it's the holy Gra question uh that one I probably won't answer in front of a camera but I am optimistic by by treating that as a whole system problem um I am optimistic we will really surprise the world on the upside good can ask on the decision making how do you guys make decisions between the two of you how do you determine what to get delegate versus what not to I think it comes back to just being really aligned on what is most important and you'll probably just hear me repeat that phrase but um things that are kind of specific to or even tangential to the most important things we really spend a lot of time on as an executive team as a leadership team trying to make the right decision around sometimes it's obvious sometimes it's not everything else gets uh gets delegated so um I probably make 10 decisions a day that don't go to Sam because they're not the most important thing um but we will spend an entire executive team meeting on one thing uh and then we'll spend the next meeting on that one thing uh if it's really the most important thing do you agree with the saying that it's like one or two decisions a year Define a company or do you agree with that you make 10 decisions a day and actually it's all about the incremental little decisions that add up to the progress of a company I'm always stuck between both mindsets I very much think it's both um I think there are one of the things that I loved about being an investor was that job is really a job about one or two decisions a year or maybe one or two decisions a decade and operator role is definitely not my natural this is not my natural place in the world by the way but in an effort to uh get slightly better at it one of the things I have learned is that it is true that there are only a handful of strategic decisions it feels more like one or two a month than one or two a year but it's not like that many like big like here is the here is the what decisions but the like the how decisions are there are a lot of those and I think people who claim there are not a lot of those have not tried to run a complex company before for because it would be ridiculous to say that any CEO makes one or two decisions a year or a month um it is really non-stop but there's a difference between like the big like we're going to do chat GPT or we're not going to do chat GPT and then the like to make that successful along the way in the spirit of making that one decision a successful one here are the 10,000 little things you have to do along the way why do you think you're not an operator I mean I'm manifestly not like I I I was I was very happy well I had a lot of fun being an investor um it's it's it's not a feeling it was not a fulfilling job for me um but it's a very fun one and and I kind of like you know all of the like things that people say to make fun of investors are somewhat true like for quality of life job it's a great great trade-off um but yeah with no false humility I'm just not an operator by Nature I'm happy to do it because I like really love open Ai and I think AI will be the most important thing I ever touch but this is not my natural fit it's just funny to hear when you think about open AI being you know the fastest going Brad would agree I'm sure would agree yeah I would definitely agree that's all you're like declined to comment no no comment on that one I love that um can I we mentioned kind of the compute element in terms of like marginal cost versus marginal revenue how do we think about when like marginal revenue exceeds marginal cost I think that's one that a lot of people suggested that we talk about today especially with llm based products obviously how do we think about that and that could be on both sides I mean truly I think of all the things we could talk about that is the most boring no offense that's the most boring question I could imagine we will really why is that boring all you have to believe is that the price of compute will continue to fall and the value of AI as the models get better and better will go up and up and like the equation works out really easily there's ways it can go wrong like if the price of comput if we don't make enough compute in the world and the supply demand thing gets out of balance and we choose for compute or by a factor of bad planning we cause compute to be really expensive then sure maybe that's um the way it goes but I think we can drive the cost of a very high quality of intelligence to very near zero and that will just be phenomenal for most things in the world not everything there will be some negatives but I think I think the cost of intelligence is about to get really really cheap how does open source and the rise of Open Source further enable that or impact that there will be a place for open source models in the world some people will want them um some people will want managed Services some people a lot of people will use both I I kind of think all of these are details that are like quite interesting in some sense but missed the bigger picture which is we are in the midst of a legitimate and pretty big technological Revolution where intelligence is going from this very limited thing which is you know smart humans have it but if you like want to do something that requires a lot of intelligence you got to get a lot of smart people to do something like if you want to make thing like open AI you need a ton of smart people a ton if you think about everything in the stack not just people who work at open a eye but the people who make chips and build data centers and all of that to something where one person will be able to access abundant and very inexpensive intelligence to do just amazing things do you think we overestimate adoption in a year and underestimate it in 10 I mean probably cuz I I think that's like actually a very deep Insight on the way that technology gets adopted in general because no matter how amazing something is societal inertia is just a big deal you only ever get a lot of adoption for something amazing but also it takes a while to get going and so that's I think you do for something cool you get the onee 10e thing so probably I think we'll have a very fast inversion of expectation reality I think right now expectations are extremely high reality is still pretty bad honestly these models are not that good uh I think very quickly expectations will start to come down as people come into contact with today's models but then very quickly also these models will get really really good and you'll see this inversion of expectations reality where all of a sudden then expectations have to catch up my question is you kind of mentioned kind of actual model quality maybe not being as good as can be and like expectation reality the other cool question which might be a little bit boring but is just the commoditization of models and I've never seen it before where you have like M draw one week so hyped and then you have you know whatever B the next and it's like the transience of different players being preceded in the meteor is kind of winning so to speak is so moving every week is this a game of commoditization there was a time when there were like more than 100 car companies in the US I believe or at least close to that and if you go like look at some of the old media at the time it was like now there's this better car now there's this better one now there's this better one and I think that same thing holds true for most new Industries I think it's fine I mean it's probably good uh but I don't think that's where the enduring value will be I think eventually it will shake out there will be a small number of providers just a relatively small number you know dozen something like that doing models at Big scale and it'll be extremely complex extremely expensive and the differentiation and I hope we all continue to push each other to make the models better cheaper faster and commoditize in that sense and the long-term differentiation will not be I don't think the base model like that's just you know intelligence is just like some emerging property of matter or something uh the the long-term differentiation will be the model that's most personalized to you that has your whole life context that plugs into everything else you want to do that's like well integrated into your life um but for now the curve is just so steep that the right thing for us to focus on is just make that base model better and better MH can I ask you you mentioned obviously your time investing and you know Brad you obviously engaged with so many large Enterprises around the world today for me as an investor I see so many AI companies and I'm not investing in any applicational AI companies because respectfully we've seen open AI come out with products and it's like well that killed the whole industry um you know I think fundamentally there are two strategies to build on AI right now or startups doing with AI there's one strategy which is assume the model is not going to get better and then you kind of like build all these little things on top of it um and then there's another strategy which is build assuming that open air is going to stay on the same rate of trajectory and the models are going to keep getting better at the same Pace um it would seem to me that 95% of the world should be betting on the latter category but a lot of the startups have been built in the former category and then when we just do our fundamental job which is make the model and its tooling better with every crank then you get the Open Eye killed my startup meme um if you're building something on open on GPT 4 that a reasonable Observer would say if gp5 is as much better as gp4 over gpt3 was not because we don't like you but just because we like have a mission we're going to steamroll you but there's a giant set of startups where you benefit from gp5 being way better and if you build those and AI progress keeps going the way that we think it's going to go I think on the most part you'll be really you'll be really for the most part you'll be really happy as an investor looking for an investment thesis that actually last what are those that will not be steamrolled that I can invest in Sam versus those that could be um ask the company whether uh a 100x Improvement in the model is something they're excited about it's actually we can tell pretty well because we know the companies that come to us saying we want the next model when is it coming out when is it coming out I want to be the first to try it it's going to be the best thing for my company then there's a lot of companies that we don't hear from on that in that regard um and I think that's like a pretty good delineation um is if there's a clear path to how better intelligence better underlying intelligence accelerates that product in that company um they should most companies can tell that story really clearly and so like CL would be an example of that CL is a good example cuz for clana I mean the numbers are astonishing and think how much better that gets if the next model is as good as we hope it's going to be I talked uh just this morning to an AI like medical adviser I guess they would call it um and they're like you know here's the places the models underperform in it's still pretty useful for like these kinds of things but if the model could just get like this much better on these metrics um we'd have all these other businesses so like can you all do that faster and then we can have like you know this like thing that'll save all these lives and give people who have not had access to Medical Care like some access and you know how soon can we get that and you know here's how many people are dying every day you delay it was an effective pitch actually that would questions beforehand that I was like I've never asked that that's like a terrible question and I'm kind of proceeding to ask most of them so I'm sorry for this but we mentioned kind of model Improvement there like how do we see the rate of model Improvement is it like linear is it like does it Plateau at points obviously now it's accelerated fast and never in the last whatever time period we want to call that how do we see that rate of improvement in models it feels very punctuated externally which means I think we've done a suboptimal job on one of our core beliefs we have this idea that iterative deployment um is important and what you don't want is to go build AGI in secret in a lab this is like the limit case toil away for a couple of decades and then push a button and all at once the world has to like contend with AGI and better than that to us it seems is to put uh you know a model out into the world let people have some time to think about that react figure out how they want to use it what they'd like it to do differently what they'd not like it to do what guardrail Society wants or doesn't want and then you know build up sort of more um societal engagement with it and I think in some sense one of the most important decisions we ever made was this one and that includes things like deploying Chach PT into the world and getting the world to take Advanced AI seriously which we tried to talk about for a long time and didn't really work and you know deploying that really did but as we think about future models uh I I think we underestimated because we've like lived with these models for so long and because we watched them get better and better little by little uh we underestimated how much even with our strategy of iterative deployment a Lurch forward some of these things would be so as we think about the next models we're trying to find a way to make that even smoother um so that it feels closer to the smoothness we feel internally uh to the external world do you think the strategy of it iterative deployment will still be possible moving forward as you get bigger and bigger you see obviously a far and llama released some on like medical scientific writing and they got terrible blowback and they had to pull it away Bard obviously did theirs and they got an 8% reduction in share price as you get bigger and bigger and bigger releasing an imperfect product can have such ramifications is that iterative deployment still possible of a time I think expectation setting matters a lot but with the right expectation setting I think it is possible yeah I would agree with that I think um we learn a lot also and so when we release Sora for example um we get an incredible amount of feedback from the creative Community from media from you know from industry and we actually started now to kind of incorporate that feedback into how we think about our research road map for that you know for that specific modality and so in a way like we we kind of start with expectations really low um we just try and learn uh and we really kind of just listen to the world and then we try and incorporate that as best we can so that by the time we actually have something we want to share it's something that really feels useful and people have kind of natural familiarity with it um and it almost feels like it was kind of built more for them um and I think that's like kind of the the mode that we'll we'll operate in somewhat here is uh is this it is really iterative um and it really is this kind of more code development with with the world maybe more than the world appreciates can I ask one final thing and then I do want to go into GTM you mentioned obviously the medical adviser earlier I hear you've got a passion for how bnny AI can solve cancer and specifically certain medical well it's more like I have a passion for how AI can help I want to say solve help like greatly increase the rate of scientific progress um and curing cancer would be a great example of that but I I do generally believe and this is like you know there's definitely just a personal element of excitement but I think science is awesome but I genuinely believe that scientific progress is like the highest order bit of progress for society economic growth quality of everyone's lives all of that and if AI can help people meaningfully increase the rate of scientific progress which I believe it will uh I think that will be a Triumph what do you think is the biggest barrier to that happening I think the models are just not smart enough which sounds like a annoying lowi information kind of copout answer but I think it's like deeply fundamentally true like the models just aren't smart enough you fix that one thing all these are things get better there will be all these ways that we have to figure how to integrate tools into people's workflow and you know modelability in different areas will will matter a lot but if you zoom out you know doing scientific research with the help of gpt2 would have seemed fairly laughable with GPT 4 people do use it just in very to to help them do science just in extremely primitive and limited ways and with GPT 6 I think people will say hey this is like helping me as a general purpose tool in all these ways and then with gp8 maybe people are like you know this can do some limited maybe not so limited tasks for me can I move to the company scaling because I think it's really important to cover I mean this is the most unprecedented company scaling really in history especially when you look at speed of Revenue growth Brad you've been at the Forefront of that it's it's a terrible question in many respects but how have you scaled so fast so efficiently and what's the secret to that and things seemingly not breaking uh well things it's always messy behind the scenes um but I appreciate you saying that on the outside at least it doesn't seem like things are breaking um well look we I think we we found a moment with Chachi BT that it people kind of it was the first like really Human Experience people have had with the technology and we hear stories all the time of like where people use it and it's continues to amaze us actually how diverse these stories are it's like on one second you're hearing like a research scientist at a company talk about how productive it's made them and the next is like this thing is writing code for me I'm a software engineer at XYZ startup and the next is like I'm a new parent and like I don't know how to take care of a baby but like I ask this thing 80 questions a day and it kind of like helps me understand how to like navigate Life as a new mom um and like the same tool can power each one of those experiences and when you have something that's like that fundamentally uh diverse um and I think that uh kind of you know fundamentally um accessible like it it's just bound to have a really important impact uh in like in adoption and you know how people use it and I think I mean that obviously translates to a business impact but our focus is is is just continuing to push on that front um the the B2B business is obviously different different different kind of um Cadence to that business um there's there's more of an adoption cycle uh in the Enterprise we've had um amazing success on the developer side so we've we've always been a company that has really prided itself I think on just we kind of build for who we know um and so we we've tried to build the best developer platform in the world for AI um Enterprises is is a new Focus for us um and so you know that that will have more of a uh there'll be more of a process to building for the Enterprise but um it's it's one that we're excited to take on and uh and so a lot more to come can ask on Talent is it bad if Talent wants to join because open AI is the hottest company it's the fastest growing company probably so everyone has to join for the mission because I'm always like does it actually we always say mission mission mission uh I mean I think it's bad just because it makes us like harder to filter uh it makes it harder for us to filter I but but yeah like I do kind of want people to think that they're doing something that's really important um I watched what has happened to other tech companies when they just become the place you want to work because it's a good resume item and you can like filter against that to varying degrees um and as you said it doesn't literally need to be to 100% true in 100% of cases but I think companies that lose their mission orientation um and get taken over by mercenaries usually come to regret that it's interesting you've invested in some of the best Founders are there any that stand out as ones that you've learned from that you've invested in and have shaped how you think about building I have been extremely fortunate to work and like be along for a small part of the ride I think with like many of the best founders of my generation and uh and I'm also happy that the they have been willing to like spend so much time now helping me uh and can I push you are there one or two that stand out and has there been a lesson or two from them chesy has been incredibly Hands-On and helpful to me over the last year and a half uh and is really good at a lot of things that uh I'm not good at and have had to like come up to speed quickly on um how to think about how we talk about our products um how to think about how to build great products uh he is really a special person uh the cison brothers are incredible and like every time I talk to them I am like that is a new deep Insight that I just never would have thought of it's like a totally nonlinear thing I invested in a lot of companies for a long time so I have like a long list of incredible ERS and that that are have been like I'm very grateful to but have been like very willing to uh really kind of like help out in different areas and I think in the same way that I tried to like learn a little bit each from a lot of different investors trying to learn a little bit each from a lot of different Founders has been uh a great strategy can I go back to usage you mentioned the kind of Divergence in usage from kind of consumers every day maybe it parents maybe it scientific researchers you've also built an incredible goto Market with some of the largest Enterprise in the world what have been some of the biggest lessons on Enterprise adoption and how large Enterprises are thinking about it approaching it adopting it that you think are noteworthy I think the biggest one is Enterprises have a very natural desire I think to want to throw the technology into a business process with the pure intent of driving a very quantifiable Roi I know what none of those words mean but it sounds great I mean I this is my joke but I can't do I could iic leas I managed my supply chain and it cost me x per year and I want to take Ai and throw it at a specific process in Supply Chain management and cut 20% of my spend out of this specific area that I spend money on that type of thing and that's great um we are here and happy to help you think through that problem I think people though criminally underrate how important it is actually and how much like return you really get on Just giving people access to the technology and that there's this kind of because you you can't quite quantify exactly how it works but like someone that used to spend 2 days doing something that now spends 2 minutes doing something and is freed up to do like 85 other things in their daily life that doesn't really show up in how you would think about Roi as an Enterprise but imagine doing that now 10,000 times over 100,000 times over how do you explain that to Enterprises CU you're right it's not like a budget line where you're like oh we got rid of X yeah it's difficult to show that supply of time shift yeah I mean part of it is just having time to show it um chbt is is a is a business product is still so new we released Enterprise back basically in you know late August September of last year and team is a sell product uh we released earlier this year so the time in Market's been virtually zero and Enterprise adoption Cycles are slower but um so I think part of it will just come with time and part of it just comes with expectations of uh your Workforce will want these tools and also like you're going to start to hire people who uh will have come from a world where they could only ever use these tools and they could use as much as they like um and they will expect to be able to use them in the workplace uh and so I think that like over time we will start to see that shift um but right now I think that's there's this kind of weird miscalibration of um of where people think they should be deploying AI That's going to have high impact with where I would say they should be deploying AI where you think the biggest companies don't ask that they should ask questions the biggest companies don't ask that they should ask yeah about how to use AI about how to integr it about concerns that they should think through a lot of companies think it's static so a lot of companies think gp4 is the best of model will ever get that's understandable every technology they've ever had to adopt has been relatively static if you think about like what the iPhone looked like you know what mobile looked like in 2009 versus today it kind of is the same thing like the form factors change a little bit they're faster they're like higher resolution but like the technolog is pretty much the same application development is pretty much the same same thing with cloud and so here they've been handed this new technology and I think their expect is like well this is it um and I think they don't ask enough about really how steep that rate of change is and like what how to think about like what the next wave of the technology will be and then the wave after that um and how to Think Through implementing that set up for that rate of change like you know we're obviously in London now uh European corporates are not that fast moving um when you change as fast as you are changing it's almost very difficult because they get used to their workflows and processes and then you change and you update and it's like oh they're all gone they're out the window do you see what I mean it's almost hard yeah no it's it is hard um and that's what makes our job hard right is I think companies have a desire to want to move that fast but there's this kind of um when you're operating at 100,000 person or 200,000 person scale it can be really really hard yeah um and so I think that'll be the the big question over the next few years for us Sam you mentioned the research of kind of culture and the importance to retain that when you bring in a go to market function and sales leaders and wholesales it's very difficult to blend kind of product and sales functions or cultures so efficiently how do you think about the challenges that one faces I think this is where Brad and I have a a great partnership in that we have different opinions about maybe how to balance any particular decision and we're I think very good at deferring to the other based off Whoever has like more context or feels like it will have a more important impact but we have really deep agreement I think in a way that many people in Brad's role wouldn't about the critical um focus of making sure that that we let Research Drive product and product Drive sales now that doesn't exclusively mean that of course there's got to be feedback the other direction and one of the reasons that we love having users now is this is like the most important reward signal you can get for if the model is good or not it's like how useful is it really to people like that that's what matters but we also know that the best thing we can do to sell more product is to make the product better and the best thing we can do to make the product better is to have a better to have better research and there's like zero disagreement between us ever on that and that is really important it's funny you mentioned the users that I was Ching to Alex Schulz from meta before and he said ask ask Sam about um growth and ask him how his mindset has been changed on growth Post open AI because it is such a a different story I think there is like Alex Schultz is a legitimate growth genius he'll be there I'm talking about this retention curve and the 30d here and the that and the This Acronym and I mean he really understands the dials of things I think you usually don't learn that much from failure you learn more From Success um but I think you also don't learn that much from like extreme break all the rules on repeatable success either and what we had with Chad GPT I would be hesitant to say I've learned anything at all about growth like have a once in a generation technological Revolution that's not really like actionable advice so if I wanted to learn about growth which I do I'm now very interested in it uh you know Alex probably can't advise me on it at this point but that's who I would normally ask why do you not learn from failure so I always disagree you learn something from failure for sure um you learn some things to exclude but at least in my own experience having failed at many many things and suc eded at some uh I have learned much more from the successes what's been your biggest learning from a success I mean so many like what to look for when hiring people um what you know I've now like I don't hire externally that often I'm like a big believer for like my direct reports I'm like a big believer and try to like promote into that when you can but certainly what to look for when promoting someone what to look for in a Founder uh I would say like yeah I can like point to my extremely long track record of failed Investments and say I made this mistake here I made this mistake there I made you know this one over there Josh Krishner asked that one he said ask him what he looks for in Founders cuz the track is so strong well all of the obvious things and then some I think some of the things that I look for uh more than other people are founders that are going after uh something that seems big if it works um I think that is way more important than people realize to like the really outlier returns so I'm you know happy to like lose nine times out of 10 and like really succeed on the 10th company rather than kind of like do okay seven times out of 10 um I think Founders that are like very good at generating lots of new ideas um Founders that have like a very fast iteration cycle obviously like you know smart and determined and all of those things matter oh great communication skills uh are something that I really look for do you okay but I've up so many I mean I've missed so many great companies but I've up because you get an engineering lead CEO and respectfully especially at seed or series a where I tend to invest they're not so honed and so they don't have that communication yeah polished I don't worry about but like as that great CEO you like like I don't mean communication and like can someone sit in an interview and be like super charismatic and you know like very you know hit the talking points and like no clearly not me either um but but I do think a lot of the job is Communications driven like you have to be able to like explain to the company what we're going to do and why and you have to be able to like hire people and get them to want to work with you and you have to be able to like sell things to customers and get people to like try your product at some point you may have to like talk to wider audiences so I I don't mean it like literally as you know can the person give a polished interview cuz I may make it my whole life without being able to do that we'll see um but in the dayto day you know able to clearly explain what you doing why people should care about it what you'd like them to do to help you uh that's super important final one before we do a quick F do you have to ask on the people that you hire at open a one thing that's quite striking is they're a little bit older actually or it certainly appears that way how do you feel about hiring for experience versus hiring people who be new to a job but may have that hustle and hunger and am I wrong to say that you hire for experiencing that little bit older um what do you think I think at least in my Works where I said hiring policy and whatnot I there's a difference between kind of what the composition of your hires are and kind of what the composition of responsibility is in the team and I I try and keep it keep this kind of um this team where like great ideas can are like kind of always elevated um and by and large actually I would say like the really really good ideas come from unexpected places on the team not from like the most experience end of the the team always and so that's kind of my advice is like find a way to make sure that there's um there's this very very flat kind of like very very even playing field when it comes to how you kind of like look to the for perspective for decision- making for for judgment um and for creativity you do need experience hires I think in that they they bring a little bit of like a little bit more perspective obviously um but I tend to think that like really the the like company changing ideas actually by and large come from places that are not not those hires do you agree I think there's like some roles where experience really matters and somewhere it either doesn't matter or is a slight negative or could be a big negative um I think like our leadership team is probably more like 30s and 40s than the 20s and 30s you would see at other startups and I think our technical people skew like slightly older um I don't have numbers but you know maybe I would guess that like the average age of the technical team is like early 30s instead of the average being like late 20s at some other tech companies I think part of that is just the sort of like path to becoming a great researcher there's huge exceptions in both sides um and I don't want to say I don't care about experience on the whole but I think there's like amazing people with tons of experience there's amazing people with like almost no experience at all I think whatever we're doing seems to be working but it's not like I don't think about it as a like do we want more or less experience I think it's very much like who is the P like is this the person I'll add one thing which is there's a lot of areas explicitly where people coming in with experience I think what we do is so categorically different like it's it is an entirely new category the way that people kind of engage with consume use talk about put you know put your verb in there uh this this technology is different so the playbooks for how you actually like bring it to the world are really different there there aren't playbooks for a lot of these things and so like the approach you take to solving problems doesn't NE you don't necessarily benefit in all ways at least in my world from people who have done it for 20 years before yeah one of the joys in new Industries is it levels the playing field it does I think you saw this in crypto in particular where suddenly 19y olds were just as impactful as a 45y old because it doesn't matter I think I think in general if you could like sample someone at open a eye you know look at the role they're doing and the level of responsibility they have and the impact they have and say you know what I have expected this person to be more experienced or less experienced given that you would say on the whole I would have expected SL maybe even hoped that this person was more experienced are you ready for a quick fire sure okay so 60 seconds or less uh per question let's start Sam what's the single biggest challenge to open AI over the next 12 months and then 5 years 30 seconds each doing the best research and the best productization of like the best Innovation on that stuff uh over the next 12 months and was it 5 years for the second thing sufficient like supply chain and computer Brad what have you changed your mind on most over the last 12 months I would say actually it really is that um the I think the rate of adoption in the Enterprise is actually going to be way faster than people realize um I think we will Buck convention on that people Enterprises having a reputation as being slow adopters of technology I think that will not be true here does that differ by geography no h do we have loads of experimental budgets do we have loads of experimental budgets well we have real budgets um and that'll help yeah uh Sam what are you most concerned about in the world today the the whole thing just feels like way more on the whole situation of the world the geopolitical thing the sort of socioeconomic stuff politics it feels more unstable to me than it has felt since I've been paying attention and there's no like one thing I would say uh that I I I I I couldn't with confidence tell you like here's the the Crux of it or here's the root cause but the the general macro instability feels High Brad what's been the most unexpected thing in the scaling of open AI for you I think it's how consistently the scaling of models has worked um it still breaks my brain uh like I don't maybe I've been we've I've watched the same trend line for six years now but I still find it incredible that uh you can make these models bigger and they get predictably better um and that is a tremendous gift bra what do you know now that you wish you'd known when you started at open AI I wish I'd appreciated the order in which the technology was going to get have impact um it it caught us somewhat by surprise how important the technology is and is going to be in Creative Industries for example um relative to more knowledge-based Industries or relative to even more industrial Industries um we were doing robotics really early on and so I Was preparing for a world where we were working with robotics companies uh and building robots and working with gaming companies and building agents we've gone completely the other way Sam what do you not do much of that you would like to do more of guess time is not particularly your friendly I don't really read anymore um I used to read a lot that's a sort of sad change would you like to make more room for it it's probably not in the cards in the short term but know someday I'm okay with this trade for now cuz I know it's not a forever thing but I have basically like run out of time for real life I don't really get to hang out with friends that much I don't get to like do the normal like life stuff and uh it is both totally a trade I'm willing to make and then again it helps to know that it won't be a forever thing but it is still just sad sorry it's a bit of a deep one are you happy I saw you know elon's I am really happy I I wouldn't say I'm having fun but I am really like deeply happy I have fun that's great good for you I mean you both also got married in the last year which is very exciting that is very exciting can you impart some wisdom on how do you retain a romantic relationship a partner happiness there where you're also I mean traveling all over the world literally every day communication I'm still learning it um it's over communicate uh be empathetic um and appreciate that like this job is uh is as taxing as probably anything uh on Earth um and the person though that is really paying the price for that is not it's not you it's it's your significant other I I look I just got 10 out of 10 lucky uh Brad the two Chris is really great but uh I think having a partner who is just sort of like this is like not what I always signed up for we used to have this like nice quiet life and uh having a partner who is just like supportive of it who gets it who's like you know what you go deal with that I'll like hang out and we'll have like a lot of time we still like make that's the kind of the one other thing I make time for but um having a supportive partner not not just supportive having like an enthusiastic partner which is like this is really important you go do this like I'll make it work I'll try to like be flexible around it um I am extremely extremely grateful did you know straight away with both of your respective partners that they were the ones for you pretty early yeah yeah uh Brad where will open AI be in 10 years I hate making 10e predictions um you can have five or 20 that help doesn't make it better um I mean I don't know pass I know Sam hates it even more than me so or we can do a both one which is like when you look forward 10 years how do you see the state of the world then and are you excited for that future State yes we wouldn't be doing this work if we weren't excited uh or at least I wouldn't but tremendously I hope that people look back and say we cannot believe how barbaric they had it in 2024 in the same way that we could look back a few hundred years or many hundreds of years and say that same thing it's like not that we're not all appreciative and grateful for life today but you know people get sick and die prematurely of disease not everybody has access to a great education not everybody kind of gets to do and spend their time the way they want um to say nothing of like the unimaginable new things that we'll have in this in this future uh again it won't be all good I think there will be like real things that we lose but on the whole I am tremendously excited for what a world with genuine abundance looks like I want to say a huge thank you for doing this honestly it's been so nice to do it in person I so love doing it with both of you so thank you both for joining me thank you having us this is great Back To Top