[Music] open AI shocked the world uh last November with uh chat GPT and um open AI is not only creating models it's uh creating the future so Sam is an honor to have you on the podcast thanks a lot for having me it's great to be here now how does it feel to spearhead this revolution ah it's definitely a little surreal it is uh it's like a very exciting moment in you know the history of technology and to get to work with the people who are who are creating this um it's like a is a great honor and uh I can't imagine anything more exciting to be doing no I can't imagine it's definitely a lot I can see that now big picture what's the vision of of the world where um humans and AI coexist well you know I one one thing that we believe is that you have to answer that question empirically there's been a lot of philosophizing about it for a long time very smart people have had very strong opinions I think they've all been wrong and it's just a question of how wrong and the course that a technology takes is is difficult to predict in advance I'm a I love that Allen K quote that the best way to invent the but the best way to predict the future is to invent it and so what we're trying to do is see where the technology takes us deploy it into the world to actually understand how people are using it where the risks are where the benefits are what people want how how they'd like it to evolve and then sort of co-evolve the technology with society and you know I think if you asked people five or ten years ago what the deployment of powerful AI into the world is going to look like they wouldn't have guessed that it looks like this um people had very different ideas at the time but this was what turned out to be where the technology leads and and where the science leads and so we try to follow that and how far into the future can you see now uh the next few years seem pretty clear to us you know we kind of know where these models are going to go we have a roadmap we're very excited about uh we can imagine both the Science and Technology but also the product a few years out and beyond that you know we're gonna learn a lot we'll be a lot smarter in two years than we are today yeah and and what kind of uh you know holy moments have you had lately um well remember that we've been you know we we've been thinking about this and playing around with this technology for a long time so the world has had to catch up very quickly but we we have less holy moments because you know we've been expecting this and we've been building it for a while and it you know we don't it doesn't feel as discontinuous to us but and what kind of big things have you seen since chat to petite sport well we the biggest ones have not been about new technology or new models but about the breadth of use cases the world is finding to do this so the holy moments have not been like oh now the model can do this now we now we figured out that because again you know some would expected that but seeing how much people are coming to rely on these models to do their work in their current form which is very imperfect and broken you know we're the first to say these models are still not very good they hallucinate a lot they're not very smart they have all these problems and yet people are using their human Ingenuity to figure out how to work around that and still leverage these tools and so watching people that are remaking their workflows for a world with llms has been big and some examples of new things you've seen new user cases applications um you know a common one is around how developers are changing their workflow to uh you know spend like half their time in chat GPT you hear people say um they feel like two or three or sometimes more product times productive than before um an uncommon one is I met a guy who runs a laundromat business as like a one-person thing and uses chat GPT for um coming up with a marketing copy dealing with like customer service uh helping review legal documents we need a long list of things and he's like I got a virtual employee in every category that was pretty cool and what about things like uh brain implants and getting it to help with speech and so on which we just saw recently um I'm very excited about neural interfaces but I am not currently super excited about brain implants I don't feel ready to want one of those I would love a device uh that could like read my mind and but I would like it to do that without having to put a hole in my skull and I think that's possible how oh there's many Technologies depending on what you'd want but you know there's there's a whole bunch of companies working on trying to sort of like read out the words you're thinking without requiring a physical implant now a few years ago nobody had heard about open AI now uh everybody's heard about it you are you know one of the most most famous people on Earth um but the people so how many people are you at open AI now 500 or so and what what do these 500 people actually do um it's a mix so there's a large Crew That's just doing the research like trying to figure out how we get from the model we have today which is very far from an AGI to an AGI and all of the pieces that have to come together there so you know scaling the models up coming up with new methods uh that that whole process uh there's a team that makes the product and figures out also how to scale it there's a sort of traditional Silicon Valley tech company go to market team um there's a very complex uh legal and policy team that does all the work you'd imagine there um yeah and so your your priorities as a CEO now how do you spend your time um I kind of think about the buckets of of what we have to do in uh research product and compute on the technical side and then uh on the and I that's sort of the work that I think I I enjoy the most and where I can contribute the most um and then I spend some of my time on policy uh and sort of social impact issues for lack of a better word uh and then the other things I spent less time on but we have great people that run the other functions now your mission has been to ensure that artificial well the general intelligence benefits all of humanity what's the biggest challenge to this you think I a couple of thoughts there uh one I'm reasonably optimistic about solving the technical alignment problem we still have a lot of work to do but you know I feel like and feel better and better over time not worse and worse this the the social part of that problem you know how do we decide whose values we align to who gets to set the rules for this how much how much flexibility are we going to give to each individual user and each individual country we think the answer is quite a lot but that comes with some other challenges um in terms of how they're going to use these systems that's all going to be uh you know difficult to put it lightly for society to agree on and and then how we share the benefits of this what we use these systems for uh that's also going to be difficult to to agree on um kind of the buckets I think about here are we've got to decide what you know Global governance over these systems as they get super powerful is going to look like and everybody's got to play a role in that um we've got to decide how we're going to share the access to these systems and we've got to decide how we're going to share the benefits of them the you know there's a lot of people who are excited about things like Ubi and I'm one of them but I have no delusion that Ubi is a full solution or even the most important part of the solution like people don't just want handouts of money from an AGI they want increased agency they want to be able to be architects of the future they want to be able to do more than they could before and figuring out how to do that while addressing all of this sort of let's call them disruptive challenges uh I think that's going to be very important but very difficult how far out this true AGI I don't know how to put a number on it I also think we're getting close enough that the definition really matters and people mean very different things when they say it but I would say that I expect by the end of this decade for us to have extremely powerful systems that change the way we currently think about the world and and you say we've got different definitions what is what is your definition of general intelligence you know there's like kind of the open AI official definitions and then there's one that's very important to me personally when we have a system that can figure out new scientific knowledge that humans on their own could not I would call that an AGI and that you think we may have by the end of this decade well I kind of tried to like soften that a little bit just by saying we'll have systems that like really change the way the world Works um the the new science may take a little bit longer or maybe not Steve what's the end game here um are we just all of us going to work a lot less um you know I want to be people I think we'll all work differently I think we'll still many of us will still work very hard but differently every technological Revolution um people say they're we're just gonna do less work in the future and we just find that we want a higher standard of living and new and different things and also that we find new kinds of work we really enjoy you know neither you nor I have to work and I bet we both work pretty hard and I love it I love my job I love my job and I feel very blessed so the definition of work what we work on why we work the reasons for it I expect that all to change what we do I expect to change but I love what I do and I expect people in the future to love even more what they do because there will be new amazing things to work on that we can hardly imagine right now and less boring stuff yeah I'm all for getting rid of the boring stuff like I think like everybody should love it that's maybe one thing we could say in the future is everybody will do things that they love you won't have to do things you don't and I think most people probably don't love their jobs right now um I believe you just traveled the world and met with a lot of people and users uh what's what was your what was your main takeaway uh uh the level of excitement about the future and what this technology is going to do for people around the world in Super different cultures and super different contexts was just very very different than I expected like it was it was like overwhelming in the in the best way any any difference between geographies yeah like you know in in the developing World um people are just focused on what this can do economically right now uh and in the more developed world there's much more of a conversation about what the downsides are going to be and you know how this is going to disrupt things and there's still excitement but it's tempered more by fear that was that was a striking change a difference do you think it will lift up the oral part of the world yeah I really do I think it's going to make everybody richer but I think it impacts positively impacts poor people the most and I think this is true for most kinds of Technology um but it should be particularly true for the democratization of intelligence you know you or I can afford to pay a super highly compensated expert if we need help but a lot of people can't and to the degree that we can make say great medical advice available to everyone um you and I benefit from that too but less less than people who just can't afford it at all right now and what would potentially prevent this from happening well we could be wrong about the trajectory that technology is on I think we are on a very smooth exponential curve that has much much further to go but you know we could be like missing something we could be drinking our own Kool-Aid we could either brick wall soon I don't think we're going to um I think we have some remarkable progress ahead of us in the next few years but yeah we could we could somehow be wrong for a reason we don't understand yet um what is it doing to the global balance of power I don't know how that's going to shift um I'm not sure anyone does but I certainly don't think that's something that I'm particularly well qualified to weigh in on but it just seems like it's being it's so key now to the the weapon race the medical race the self-driving vehicle race just all these races but it's also available pretty broadly you know like one of the things that we think is important is that we make gpt4 extremely widely available um even if that means people are going to use it for things that we might not always feel are the best things to do with it uh but you know we have a goal of globally democratizing this technology and as far as we know gpt4 is the most capable model in the world right now and it is available to anyone who wants to pay what I think are the very cheap API rates now anyone is not quite there you know we don't we're blocked in a hand we block a handful of countries that the US has embargoes with or whatever but it's pretty available to the world but in order to develop it further you need um well you need the right chips right and they are not available but what matters is how you're going to get to like GPT six and seven and also even more than that how you're going to get the next set of very different ideas that take you on a different trajectory like everyone knows how to climb this one Hill and we're gonna go figure out the next total Decline and there's not a lot of people in the world that can do that but we're committed to making that as widely available as we can do we know where China is here we don't maybe someone doesn't want here do you think there's a chance that well like they did with weapons that just suddenly bang they had the supersonic Rockets we didn't even know they existed right could that happen yeah totally it could I mean we're gonna work as hard as we can to make sure that we stay in the lead but we're a little in the dark so Mark Andreessen for instance he thinks we should stuff it into everything and you know as part of the geopolitical fight what do you think stuff it into everything I mean just like put it everywhere that's happening and I think that's great like without revealing something I shouldn't the amount of gpt4 usage and the number of people companies that are integrating it into different ways is staggering is awesome some examples if you had to reveal something uh I mean like you know car makers are putting it into cars and I was like all right that sounds like a gimmick and then I got to try a demo of it and I was like wow this being able to just talk to my car and control it in a sophisticated way entirely by voice actually totally changes my experience of how I like use a car in a way that I would not have believed was so powerful so for instance use it in a car what do you say uh this is this is probably where I don't want to like reveal a partner's plans but you can imagine a lot of things that you might say like the basic stuff is easy like you know I need to go here and um I'd like to listen to this music and also can you make it colder um sounds good do you depend on uh newer and even more powerful ships than what we have now I mean how much quicker do you how much more complex the chips need to be than h100 or the latest things from Nvidia um yeah of course like there's the ways the ways that we can keep making these models better are we can come up with better algorithms or just more efficient implementations or both we can have uh better chips and we can have more of them and we plan to do all three things and they multiply together and do you think these the chip makers who will end up with the profits there uh they will end up with profits I wouldn't say the prophets I think there's many people who are gonna like share this massive economic boon how much does it cost to train these models I mean how much have you spent on free training models we don't really talk about exact numbers but like quite a lot yeah and what's the challenge of spending so much money pre-training and then it lasts for a relatively short period of time in a way you have to depreciate the whole investment in order because you need to invest more in the Next Generation uh I mean what are the what's yeah how do you think how do you think about this I that's true I don't think they're going to be as many massive pre-trained models in the world as people think I think there will be a handful and then a lot of people are going to fine-tune on top of that or whatever so so how does how do you how do you read the competitive part of it that I think is important is like you know when we did do gpt4 um we did we produced this artifact and people use it and it generates all this economic value and um you're right that does depreciate fast but in the process of that we learned so much about how to go we pushed the frontier of research so far forward and we learned so much that it'll be critical to us being able to go do gpt5 someday or whatever that it's like you're not just depreciating the capex one time for the model you have generated a huge amount of new IP to help you keep keep making better models um so the way you read the competitive landscape now how what does it look like uh I mean there are going to be many people making great models will be one of them we'll like contribute our egi to the world to society among among others and I think that's fine and you know we'll all run different experiments we'll try setting you know we'll have different features different capabilities we'll have different opinions about what the rules of a model should be and through the magic of competition uh and users deciding what they want we'll get to a very good place how far ahead do you think you are a competition I don't know I don't think about that much to be honest like we're our customers are very happy uh they are desperate for more features and more capacity and us to be able to deliver our service in all of these little better ways and we're very focused on that um I'm sure Google will have something good here at some point but like I think they're you know racing to catch up with where we are and we're thinking very far ahead of that so normally in in the software business you have something which is very cheap where you ship where you ship a lot of it or something which is very expensive and you don't ship so much here you could potentially ship something and I can see you smiling here hey you can potentially exactly so so tell us how how is this going to work you know I'll tell you one of the most fun things about this job is we are past the point as a company uh I am past the point as like a CEO running this company where there's like a road map to follow we're just doing a bunch of things that are like outside of the standard Silicon Valley received wisdom and so we get to just say well we're going to figure it out and we're going to try things and if we got it wrong like who cares there was no like it's not like we like screwed up something that was already figured out I mean back to our very founding like most big tech companies are a they start as a product company and eventually they built on a research lab that doesn't work very well and we started as a research lab and then bolted on a product company that didn't work very well and now we're making that better and better um but to like a project company I mean Microsoft no no I mean like having to figure out how to ship the API in chat GPT yeah um like we started we really did just start as a research lab and then one day we're like we're gonna make a product and then we're gonna make another product and now that product is like the fastest growing product in history or whatever and we weren't set up for that it's the usage of chatipity decelerating no I think it maybe took like a little bit of a flat line during the summer which happens for lots of products but it is doink up tell us about the relationship with Microsoft how does that work um I mean at a high level they build us computers we train models and then we both use them and it's a pretty clear and great partnership are you have you are your goals aligned yeah they really are um one of I mean there's like there's of course areas where we are not perfectly aligned and like I don't like any partnership in Life or business or whatever I won't pretend it's perfect but it is very good and we are aligned at the highest levels which is really important and the the misalignments that come up at the sort of lower levels once in a while we you know like no contract in the world is what makes a partnership good like what makes a partnership good is that when those things happen you know Satya and Kevin and I talk and you'd figure it out and you know there's like a good spirit of compromise over a long time now they've been one of them initiators and I mean together with you in terms of self-regulating this space what can this type of thing be self-regulated not entirely um I think it needs to start that way and I think that's also kind of like how you figure out a better answer but like governments are going to have to do their own thing here and you know we can provide input to that but we don't we're not like the elected decision makers of society and we're very aware of that and what can governments do anything they want um and I think people forget this like governments have quite a lot of power they just have to decide to use it yeah but I mean so let's say now Europe decides that they're going to regulate you really harshly I mean are you just going to say goodbye Europe no possibly um I don't think that's what's gonna happen like I think we have a very productive conversation I think Europe will regulate AI but reasonably not not very harshly and what is I'm sorry and what is a reasonable regulation what what is that level I think there's many ways it it could I think there's many ways that it could go uh that would all be reasonable but you know like to give one specific example and I'm surprised this is controversial at all but a regulatory thing that's coming up a lot in Europe and elsewhere is that if you're using an AI you've got to disclose it so if you're talking to like a bot and not a person you need to know that that seems like a super reasonable and important thing to do to me for a bunch of reasons given what's starting to happen um to my surprise there's some people who really hate that idea but I'd say that's like a very very um reasonable regulation I agree I agree do you think we'll get Global regulation is there any um shape I think that can happen I think we're going to get it for only the most powerful systems so you know I think like individual countries or blocks of countries are not going to give up their right to self-determine for like you know what can a model say and not say and how do we think about the Free Speech rules and whatever um but but for technology that is capable of causing Grievous harm to the entire world like we have done before with nuclear weapons a small number of other examples yeah I think we are going to come together and get good Global regulation but given how embedded it now is in in everything as we spoke about you know weapons your car you're sitting in your car and it's like super cool and it's uh cold and hot than music and this and that and you know and you you're a Chinese car company and you won't all compete the the Americans why would you wanna why would you only when you want to have a regular regulation on this well gpt4 I don't think needs Global regulation nor should it have it I'm talking about like what happens when we get to gpt10 and it is you know say smarter than all of humans put together and that's why you think we get it that's when I think we'll get it when you have the cost of Intelligence coming down so dramatically like it is now what is it going to do to productivity in the world I mean it's supposed to go up a lot right that's what theory tells us and that's what I think so so um I've told everybody in in our company that hey we shouldn't we should improve our productivity about 10 over the next 12 months all of us and that's and you know how I got the number did you ask gbt no I just took it I just took it straight out of the air do you think what do you think about that number is it low high under ambitious what what should what should productivity increase by how do you how do you measure uh the stuff we do that's not very good measurement but just the kind of stuff that I produce how much of your company writes code uh if uh 15 well people in in technology probably 15 20 of us more actually but okay let's let's say that's 20 writing code I think an overall goal of like you know 20 productivity increase in a 12-month period is appropriately ambitious given the tool and given the tools that we will launch over the next 12 months okay sounds like I should uh up the game her a bit I think so yeah I'll just tell everybody you told me to so that's fine it's better to set a goal that is like slightly too ambitious than significantly under ambitious in my opinion yeah um now is there like a an inherent limitation to what AI can achieve I mean is there like a point of no further progress I couldn't come up with any reasonable explanation of why that should be the case you say um that most people overestimate risk and underestimate reward what do you mean by that um you know there's a lot of people that don't go start the company or take the job they want to take or try a product idea because they think it's too risky and then if you really ask them like all right can we unpack that and can you explain what what the risk is and what's going to go wrong it's like well the company might fail okay and then what you know well then I have to go back to my own job my old job all right that seems reasonable and they're like well you know but I'll be a little embarrassed and I'm like oh is that you know what's the cause I I I think like people view that as a super risky thing and they view staying in a job where they're not really progressing or learning more or doing new things for 20 years uh it's not risky at all and to me that seems catastrophically risky you know to like miss out on 20 years of your very limited life and energy to try to do the thing you actually want to do um that seems really risky [Music] but it's not thought of that way talking about staying in your job what um so the leaders and the CEOs so you know how how is AI going to change the way leaders need to act and behave well hopefully it's gonna like do my job you know hopefully the first thing we do with AGI is let it run open Ai and I can you know go sit on the beach that'd be great I wouldn't want to do that for long but right now it sounds really nice how do you develop the people in your company how do you develop your leaders um I think developing leaders tend to fail at the same set of things most of the time you know they don't they don't spend enough of their time hiring talent and developing their own teams they don't spend enough of their time articulating and communicating the vision of their team uh they don't spend enough of their time thinking strategically because they get bogged down on the details and so when I like put a new person in a very senior role which I always try to do with promotions I mean I'm willing to hire externally but I'd always always rather promote internally um I have them over for dinner or go for a walk or sit down or something and say like here are the ways you're going to screw up I'm gonna tell you all of them right now you're gonna totally ignore me on this and not believe me or at least not do them because you're going to think you know better or you know not make these mistakes but I'm going to put this in writing and hand it to you and we're going to talk about it in three months and in six months and you know eventually I think you'll come around and they always ignore me and always come around and I think just like letting people recognize that for themselves uh but telling them up front so that it's at least in their mind is very important well it's the most common way leaders grow up uh failing to recruit slash promote and then failing to build a good delegation process and then as a consequence of those not having enough time to set strategy because they're too bogged on in the day-to-day and they can't get out of that downward spiral uh what what is your delegation process look like two things number one high quality people number two setting the training wheels at the right height and increasing them over time as people learn more and I build up more Trust is that the way to manage geniuses um they get uh researchers that's a different thing I was like talking about how to like Executives that run the thing okay what about researchers what about the geniuses um the primadonna's explain well pick really great people explain the general direction of travel and the resources that we have available and kind of at a high level where we need to get to to get to the next level so you know we have to achieve this to go get the next 10 times bigger computer or whatever and you know provide like the most mild input on it would be really great if we could pursue this research Direction and this would be really helpful and then step back so we kind of like you know we set a very high level vision for the company and what we want to achieve and beyond that researchers get just a huge amount of freedom do you think companies generally are too detailed in the remit they give the teams yes I mean at least for our kind of thing I think uh managing we talked earlier about having to like ReDiscover a bunch of things I'd say this realizing it's going to come across as arrogant and I don't mean it that way but I think it's an important Point um there used to be great research that happened in companies in Silicon Valley um you know Xerox park being the obvious example there have not been for a long time and we really had to ReDiscover that and we made many screw-ups along the way to learn how to run a research effort well and how you balance letting people go off and do whatever towards trying to get the company to point in the same direction and then over time how to get to a culture where people will try lots of things but realize where the promising directions are and on their own want to come together to say let's put all of our Firepower behind this one idea because it seems like it's really working you know I'd love to tell you we always knew language models were going to work that was absolutely not the case we had a lot of other ideas about what might work but when we realized the language models were going to work we were able to get the entire research trust or almost entire research Brain Trust to get behind it I'm slightly surprised you say that there was no innovation culture in Silicon Valley because that's uh a bit contrary to uh to what I thought so there is yeah there's a product Innovation culture for sure a good one but like I mean again I hate to say this because it sounds so arrogant but like before open AI what was the last really great scientific breakthrough that came out of a Silicon Valley company and and why did and why did that happen why what happened there well we got a little lucky no I don't mean we I'm sorry why did why do these culture disappear in Silicon Valley you think I have spent so much time reflecting on that question uh I don't fully understand it I think I think it got so easy to make a super valuable company um and people got so impatient on timelines and return Horizons that a lot of the capital went to these things that could just you know fairly reliably multiply money in a short period of time uh by just saying like we're gonna take the magic of the technology we have now the internet mobile phones whatever and apply to every industry that sucked up a lot of talent very understandably now you you had some um what should we say you'll you'll co-founders are pretty pretty into big big hairy goals right yeah I mean we're trying to make AGI I think that's the biggest hairiest goal in the world so not so many companies have those kind of co-founders and people who with that kind of track record and you know that that type of talent magnet uh funding capabilities and so on do you how important was that you mean Elon by this right yeah yeah and you know and some of the other people you worked in the beginning well there were there's six co-founders uh Elon and me Greg and Elia and John and voichak and you know Elon was definitely a talent magnet and attention magnet for sure and also just like has some real superpowers that were super helpful to us in those early days aside from all of those things and you know contributed in ways that we're very grateful for but the rest of us were like pretty pretty unknown and I mean maybe I was like somewhat known in technology circles because I was running my combinator but not not like a not in a major way uh and so we just had to like you know grind it out but that was like that was like a good and valuable process what is your superpower I think I'm good at thinking very long term and not being sort of constrained in like common common wisdom evaluating talent that was like a really helpful thing to learn from my combinator you said in 2016 that long-term thinking it's a competitive Advantage because almost no one does it yeah I mean when we started openai and said we're going to build AGI everybody was like that's insane hey it's 50 years away and B it's like you know the wrong thing to even be thinking about you should be thinking about this how to improve this one thing this year you know also this is like unethical to even say you're working on it because it's like such a science fiction and you're gonna lead to another AI winter because it's too much hype and we just said it's going to take us a while but we're going to go figure out how to do it you said you was a good at assessing Talent what how do you do it I don't know I don't I can't like I have a lot of practice so I've got like a but I don't have like words for it I can't I can't tell you like here's the five questions I ask or here's the one thing I always look for but you know assessing if someone is smart and if they have a track record of getting things done and if they have like novel ideas that they're passionate about I think you can learn how to do that through thousands of conversations even if it's hard to explain why is Europe um so behind generally when it comes to Innovation and Innovative culture I'd ask you that I don't know why is it what is it first of all like well I guess I guess it is uh look at where the big tech companies are where the big Innovations come uh it's certainly behind it's certainly very behind in like hyperscale software companies there's no question there but big fear of failure uh it's a cultural thing um it's there's a lot of there's there are a lot of things going into that cocktail I think the the fear of failure thing um and and the kind of the like the cultural environment or backdrop there is is huge no doubt uh the you know we funded a lot of European people at YC and a thing they would always say is like they cannot get used to the fact that in Silicon Valley failure is tolerated field and stuff big time and I'm sure I'll fail at stuff in the future what was the biggest failure so far uh well I mean monetarily wise I've made a lot of big Investments that have gone to Total like just you know zero like crater in the ground but in terms of like time and psychological impact on me I did a startup from when I was like 19 to 26. worked unbelievably hard to consume my life and failed at that and that was like quite painful and quite demoralizing and it's like it you know you learned to get back up after stuff like that but it's hard how do you get back up um I mean one of the key insights for me was realizing that although I thought this was like terribly embarrassing and shameful uh no one but me spent much time thinking about it who do you ask for advice like personally my strategy is not to just have like one person that I go to with everything and a lot of people do that you know they have like One Mentor that they go to for every big decision but my strategy is to talk to a ton of different people when I'm facing a big decision and try to synthesize the input from all of that so if I'm facing like a real major strategic challenge for openai um you know kind of one of these better company things I would bet that you know counting people internal and external the company I talked to 50 people about it and probably out of you know 30 of those conversations I would hear something interesting or learn something that updates my thinking and that's my strategy so now outside AI um what are you the most excited about Fusion I think we're going to get Fusion to work very soon and I think my model if you boil everything down to get to abundance in the world the two biggest most important things are bringing the cost of intelligence way down and bringing the cost and amount of energy way down and I think AI is the best way to do the former and fusion is the best way to do the latter and you know in a world where we look at energy that's like less than a penny per kilowatt hour and more importantly we can have as much as we want and it's totally clean um that's a big deal do you think it's going to solve the climate problem yes we'll have to use it to do other things like we'll have to you know use some of it to capture carbon because we've already done so much damage but yes I do what about crypto uh I am excited for the vision of crypto and it has so far failed to deliver on that promise but you have plans it's it's not something I'm spending that much time like open air is taking over my whole life so I can have a lot of plans about open Ai and there's other projects that I've invested in or helped start that I feel bad because I don't have much time to offer them anymore but they're all run by super capable people and I assume they'll figure it out what do you read um the thing that has unfortunately gone the most by the Wayside for me recently has been free time and thus reading so I don't I don't get to read much these days uh I used to be a voracious reader and uh there was like one year where I read you know not fully but like more than a scam I Read 50 textbooks and that was like an unbelievable experience uh but I don't like this last year uh I have not read many books what's the one book young people should read that's a great question picking one is really hard um I don't think man that's such a good question um I don't think it's the same for every young person uh and I like coming up with a generic singular recommendation here is super hard I don't think I can give a faithful answer on this one it's good now we uh we are uh fast forwarding you know what it's not can I actually I do have this is not the one for every young person but I wish a lot more people would read the beginning of infinity early on in there early on in their career or their lives the beginning of infinity the beginning of infinity bye I think uh that doesn't matter we'll find it I think it's the most inspiring you can do anything you can solve any problem and it's important to go off and do that it's a very like I felt it was like a very expansive book of the way I thought about the world well Sam I think that's a very beautiful place to uh to go in for landing now last one so um fast forward a couple of decades um people sit down and reflect on Sam oldman's impact on the attack world and Society what what do you hope what do you hope they'll say what do you what do you hope your lazy will be you know I'll think about that when I'm like at the end of my career like right now I my days are spent like trying to figure out why this executive is mad at this one and why this product is delayed and like why our Network on our you know big new training computer is not working and who screwed that up and how to fix it and it's like very caught up in the like annoying tactical problems uh there is no room to think about Legacy we're just trying to go off and like build this thing fantastic well um good luck with that it's been been absolutely fantastic conversation and uh all the best of luck and uh go get them great talking to you thank you for thank you for having me [Music] me