Wojciech Zaremba: OpenAI Codex, GPT-3, Robotics, and the Future of AI | Lex Fridman Podcast #215
the following is a conversation with wojciech zaramba co-founder of openai which is one of the top organizations in the world doing artificial intelligence research and development wojciech is the head of language and cogeneration teams building and doing research on github copilot openai codex and gpt three and who knows four five six n and n plus one and he also previously led openai's robotic efforts these are incredibly exciting projects to me that deeply challenge and expand our understanding of the structure and nature of intelligence the 21st century i think may very well be remembered for a handful of revolutionary ai systems and their implementations gpt codex and applications of language models and transformers in general to the language and visual domains may very well be at the core of these ai systems to support this podcast please check out our sponsors they're listed in the description this is a lex friedman podcast and here is my conversation with wachek zaremba you mentioned that sam altman asked about the fermi paradox and the people at open ai had really sophisticated interesting answers so that's when you knew this is the right team to be working with so let me ask you about the fermi paradox about aliens why have we not found overwhelming evidence for aliens visiting earth i don't have a conviction in the answer but rather kind of probabilistic perspective on what might be a let's say possible answers it's also interesting that the question itself even can't touch on the you know your typical question of what's the meaning of life because like if you assume that like we don't see aliens because they destroy themselves that kind of upwards their focus on making sure that we won't destroy ourselves yeah and at the moment the place where i am actually with my belief and these things also change over the time is i think that we might be alone in the universe which actually makes life more or less a consciousness life more kind of valuable and that means that we should more appreciate it have you always been alone so what's your intuition about our galaxy our universe is it just sprinkled with graveyards of intelligent civilizations or are we truly is is life intelligent life truly unique at the moment my belief that it is unique but i would say i could also you know there was like some footage released with ufo objects which makes me actually doubt my own belief yes yeah i can tell you one crazy answer that i have heard yes so apparently when you look actually at the limits of computation you can compute more if the temperature of the universe would drop down so one of the things that aliens might want to do if they are truly optimizing to maximize amount of compute which you know maybe can lead to or let's say simulations or so it's instead of wasting current entropy of the universe because you know we by living we are actually somewhat wasting entropy then you can wait for the universe to cool down such that you have more computation that's kind of a funny answer i'm not sure if i believe in it but that would be one of the reasons why you don't see aliens it's also possible see some people say that maybe there is not that much point in actually going to other galaxies if you can go inwards so there is no limits of what could be an experience if we could you know connect machines to our brains while there are still some limits if we want to explore universe yeah there could be a lot of ways to go inwards too once you figure out some aspect of physics we haven't figured out yet maybe you can travel to different dimensions i mean travel in three-dimensional space may not be the most fun kind of travel there may be like just a huge amount of different ways to travel and it doesn't require a spaceship going slowly in 3d space space time it also feels you know one of the problems is that speed of light is low and universe is vast yeah and um it seems that actually most likely if we want to travel very far then then we would instead of actually sending spaceships with humans that wait a lot we would send something similar to what yuri miller is working on these are like a huge uh sail which is at first powered power there is a shot of laser from an earth and it can propel it to a quarter of speed of light and uh sail itself contains a few grams of equipment and that might be the way to actually transport matter through universe but then when you think what would it mean for humans it means that we would need to actually put their 3d printer and you know 3d print a human on other planet i don't know play them youtube or let's say or like a pre 3d print like a huge human right away or maybe a womb or so um yeah with our current techniques of archaeology if a civilization was born and died long long enough ago on earth we wouldn't be able to tell and so that makes me really sad and so i think about earth in that same way how can we leave some remnants if we do destroy ourselves how can we leave remnants for aliens in the future to discover like here's some nice stuff we've done like wikipedia and youtube do we have it like in a satellite orbiting earth with a hard drive like how how do we say how do we back up human civilization uh for the good parts or all of it is good parts so that uh it can be preserved longer than our bodies can that's a that's kind of a it's a difficult question it also requires the difficult acceptance of the fact that we may die and if we die we may die suddenly as a civilization so let's see i think it kind of depends on the cataclysm we have observed in other parts of the universe that births of gamma rays these are high energy rays of light that actually can apparently kill entire galaxy so there might be actually nothing even to nothing to protect us from it i'm also when i'm looking actually at the past civilization so it's like aztecs or so they disappear from the surface of the earth and one can ask why is it the case and the way i'm thinking about it is you know that definitely they had some problem that they couldn't solve and maybe there was a flat and all of a sudden they couldn't drink there was no potable water and they all died and i think that so far the best solution to such a problems is i guess technology so i mean if they would know that you can just boil water and then drink it after then that would save their civilization and even now when we look actually at the current pandemic it seems that once again actually science comes to rescue and somehow science increases size of the action space and i think that's a good thing yeah but nature has a vastly larger action space but still it might be a good thing for us to keep on increasing action space okay looking at past civilizations yes but looking at the destruction of human civilization perhaps expanding the action space will add actions that are easily acted upon easily executed and as a result destroy us so let's see i was pondering why actually even we have negative impact on the globe because you know if you ask every single individual they would like to have clean air they would like healthy planet but somehow it actually is not the case that as a collective we are not going this direction i think that there exists very powerful system to describe what we value that's capitalism it assigns actually monetary values to various activities at the moment the problem in the current system is that there are some things which we value there is no cost assigned to it so even though we value clean air or maybe we also value lack of destruction on the internet or so at the moment these quantities you know companies corporations can pollute them uh for free so in some sense i wish or like and that's i guess purpose of politics to align the incentive systems and we are kind of maybe even moving in this direction the first issue is even to be able to measure the things that we value then we can actually assign the monetary value to them yeah and that's so it's getting the data and also probably through technology enabling people to vote and to move money around in a way that is aligned with their values and that's very much a technology question so like having one president and congress and voting that happens every four years or something like that that's a very outdated idea there could be some technological improvements to that kind of idea so i'm thinking from time to time about these topics but it also feels to me that it's it's a little bit like a it's hard for me to actually make correct predictions what is the appropriate thing to do i extremely trust uh sam altman our ceo on these topics he um okay i'm more on the side of being i guess naive hippie that yeah that's your life philosophy um well like i think self-doubt and uh i think hippie implies optimism those those two things are pretty pretty good way to operate i mean still it is hard for me to actually understand how the politics works or like uh how this like exactly how the things would play out and sam is a really excellent with it what do you think is rarest in the universe you said we might be alone what's hardest to build is another engineering way to ask that life intelligence or consciousness so like you said that we might be alone which is the thing that's hardest to get to is it just the origin of life is it the origin of intelligence is it the origin of consciousness so um let me at first explain you my kind of mental model what i think is needed for life to appear um so i imagine that at some point there was this primordial zoop of amino acids and maybe some proteins in the ocean and you know some proteins were turning into some other proteins through reaction and you can almost think about this uh cycle of what turns into what as there is a graph essentially describing which substance turns into some other substance and essentially life means that all the sudden in the graph has been created a cycle such that the same thing keeps on happening over and over again that's what is needed for life to happen and in some sense you can think almost that you have this gigantic graph and it needs like a sufficient number of edges for the cycle to appear then um from perspective of intelligence and consciousness my current intuition is that they might be quite intertwined first of all it might not be that it's like a binary thing that you have intelligence or consciousness it seems to be a more a continuous component let's see if we look for instance on the even networks recognizing images and people are able to show that the activations of these networks correlate very strongly with activations in visual cortex of some monkeys the same seems to be true about language models also if you for instance look if you train agent in a 3d world at first you know it it it it barely recognizes what is going on over the time it kind of recognizes foreground from a background over the time it kind of knows where there is a foot and it just follows it over the time it actually starts having a 3d perception so it is possible for instance to look inside of the head of an agent and ask what would it see if it looks to the right and the crazy thing is you know initially when the agents are very trained these predictions are pretty bad over the time they they become better and better you can still see that if you ask what happens when the head is turned by 360 degrees for some time they think that the different thing appears and then at some stage they understand actually that the same thing's supposed to appear so they get like a understanding of 3d structure it's also you know very likely that they have inside some level of and of like a symbolic reasoning like they're particularly symbols for other agents so when you look at dota agents they collaborate together and uh and now they they they have some anticipation of uh if if they would win battle they have some some expectations with respect to other agents i might be you know too much anthropomorphizing um the the how the things look look for me but then the fact that they have a symbol for other agents and makes me believe that at some stage as the uh you know as they are optimizing for skills they would have also symbol to describe themselves this is like a very useful symbol to have and this particularity i would call it like a self-consciousness or self-awareness and still it might be different from the consciousness so i guess the the way how i'm understanding the word consciousness let's say the experience of drinking a coffee or let's say experience of being a butt that's the meaning of the word consciousness it doesn't mean to be awake yeah it feels it might be also somewhat related to memory and recurrent connections so um it's kind of okay if you look at anesthetic drugs they might be uh like they essentially they disturb brain waste such that [Music] maybe memory is not not formed so there's a lessening of consciousness when you do that correct and so that's one way to intuit what is consciousness there's also kind of another element here it could be that it's you know this kind of self-awareness module that you described plus the actual subjective experience is a storytelling module that tells us a story about uh what we're experiencing the crazy thing so let's say i mean in meditation they teach people not to speak story inside of the head and there is also some fraction of population who doesn't have actually narrator i know people who don't have a right narrator and you know they have to use external people in order to kind of solve tasks that require internal narrator so it seems that it's possible to have the experience without the talk what are we talking about when we talk about the internal narrator is that the voice when you're like yeah i thought that that that's what you are referring to well i was referring more on the like not an actual voice i meant like there's some kind of like subjective experience feels like it's it's fundamentally about storytelling to ourselves it feels like like the feeling is a story that is much much simpler abstraction than the raw sensory information so it feels like it's a very high level abstraction that is useful for me to feel like entity in this world most useful aspect of it is that because i'm conscious i think there's an intricate connection to me not one wanting to die so like it's a useful hack to really prioritize not dying like those seem to be somehow connected so i'm telling the story of like it's richly feels like something to be me and the fact that me exists in this world i want to preserve me and so that makes it a useful agent hack so i will just refer maybe to the first part as you said about the kind of story of describing who you are i was thinking about that even so you know obviously i'm i'm i like thinking about consciousness uh i like thinking about the ai as well and i'm trying to see analogies of these things in ai what would it correspond to so um you know openly i trained a a model called gpt which can generate a pretty amusing text on arbitrary topic and um and one way to control gpd is uh by putting into prefix at the beginning of the text some information what would be the story about you can have even chat with uh you know with gpt by saying that the chat is with lex or elon musk or so and gpt would just pretend to be you or elon musk or so and it almost feels that this uh story that we give ourselves to describe our life it's almost like a things that you put into context of gpt yeah the primary it's the and but the the context we provide to gpt is uh is multimodal it's so gpt itself is multimodal gpt itself uh hasn't learned actually from experience of single human but from the experience of humanity it's a chameleon you can turn it into anything and in some sense by providing context uh it you know behaves as the thing that you wanted it to be and it's interesting that the you know people have a stories of who they are and as i said these stories they help them to operate in the world but it's also you know interesting i guess various people find it out through meditation or so that there might be some patterns that you have learned when you were a kid that actually are not serving you anymore and you also might be thinking that that's who you are and that's actually just the story yeah so it's a useful hack but sometimes it gets us into trouble it's a local optima you wrote that stephen hawking he tweeted stephen hawking asked what breathes fire into equations which meant what makes given mathematical equations realize the physics of a universe similarly i wonder what breathes fire into computation what makes given computation conscious okay so how do we engineer consciousness how do you breathe fire and magic into the machine so it seems clear to me that not every computation is conscious i mean you can let's say just keep on multiplying one matrix over and over again and my gigantic matrix you can put a lot of computation i don't think it would be conscious so in some sense the question is what are the computations which could be conscious uh i mean so one assumption is that it has to do purely with computation that you can abstract away matter and other possibilities that it's very important was the realization of computation that it has to do with some uh uh force fields or so and they bring consciousness at the moment my intuition is that it can be fully abstracted that way so in case of computation you can ask yourself what are the mathematical objects or so that could bring such a properties so for instance if we think about the models uh ai models then what they truly try to do or like models like gpt is uh you know they try to predict a next word or so and this turns out to be equivalent to compressing text and because in some sense compression means that you learn the model of reality and you have just to uh remember where are your mistakes the better you are in predicting the and and in some sense when we look at our experience also when you look for instance the car driving you know in which direction it will go you are good like a in prediction and um you know it might be the case that the consciousness is intertwined with compression it might be also the case that self-consciousness has to do with compressor trying to compress itself so um okay i was just wondering what are the objects in you know mathematics or computer science which are mysterious that could uh that that could have to do with consciousness and then i thought um you know you you see in uh mathematics there is something called cadal theorem which means okay you have if you have sufficiently complicated mathematical system it is possible to point the mathematical system back on itself in computer sense there is uh something called helping problem it's it's somewhat similar construction so i thought that you know if we believe that that the that under assumption that consciousness has to do with uh with compression uh then you could imagine that the the as you keep on compressing things then at some point it actually makes sense for the compressor to compress itself metacompression yeah consciousness is metacompression that's uh that's and i and an idea and in some sense you know the creation of it thank you so uh but do you think if we think of a touring machine a universal touring machine can that achieve consciousness so is there some thing beyond our traditional definition of computation that's required so it's a specific computation and i said this computation has to do with compression and the compression itself maybe other way of putting it is like you are internally creating the model of reality in order like a it's like a you try inside to simplify reality in order to predict what's going to happen and that also feels somewhat similar to how i think actually about my own conscious experience so clearly i don't have access to reality the only access to reality is through you know cable going to my brain and my brain is creating a simulation of reality and i have access to the simulation of reality are you by any chance uh aware of uh the harder prize marcus hutter he he made this prize for compression of wikipedia pages and there's a few qualities to it one i think has to be perfect compression which makes i think that little quirk makes it much less um applicable to the general task of intelligence because it feels like intelligence is always going to be messy uh like perfect compression is feels like it's not the right goal but it's nevertheless a very interesting goal so for him intelligence equals compression and so the smaller you make the file given a large wikipedia page the more intelligent the system has to be yeah that makes sense so you can make perfect compression if you store errors and i think that actually what he meant is you have algorithm plus errors and by the way hooter hatter is a he was pa uh phd advisor of shenleck who is the mind uh uh deep mind co-founder yeah yeah so there's an interesting and now he's a deep mind there's an interesting uh network of people he's one of the people that i think seriously took on the task of what would an agi system look like i think for a longest time the question of agi was not taken seriously or rather rigorously and he did just that like mathematically speaking what would the model look like if you remove the constraints of it having to be having to have a reasonable amount of memory reasonable amount of running time complexity uh computation time what would it look like and essentially it's it's a half math half philosophical discussion of uh how would like a reinforcement learning type of framework look like for an agi yeah so he developed a framework even to describe what's optimal with respect to reinforcement learning like there is a theoretical framework which is as you said under assumption there is infinite amount of memory and compute and there was actually one person before his name is solomonov hutter extended amount of work to reinforcement learning but there exists a theoretical algorithm which is optimal algorithm to build intelligence and i can actually explain you the algorithm yes let's go let's go so the task itself can i just pause how absurd it is for brain in a skull trying to explain the algorithm for intelligence just go ahead it is pretty crazy it is pretty crazy that you know the brain itself is actually so small and it can ponder how to design algorithms that optimally solve the problem of intelligence okay all right so what's the algorithm so let's see so first of all the task itself is described as you have infinite sequence of zeros and ones okay you read n bits and you are about to predict n plus one bit so that's the task and you could imagine that every task could be casted as such a task so if for instance you have images and labels you can just turn every image into sequence of zeros and ones then label you concatenate labels and you and that that's actually the the and you could you could start by having training data first and then afterwards you have test data so theoretically any problem could be casted as a problem of predicting zeros and ones on this infinite type so um so let's say you read already n bits and you want to predict n plus one bit and i will ask you to write every possible program that generates these end bits okay so and you can have you you choose programming language it can be in python or c and the difference between programming languages might be there is a difference by constant asymptotically your predictions will be equivalent so you you read and beats you enumerate all the programs that produce these and end bits in their output and then in order to predict n plus one bit you actually weight the programs according to their length and there is like some specific formula how you weight them and then the n plus one bit prediction is the prediction uh from each of this program according to that weight like statistically you statistically pick so the smaller the program the more likely you you are to pick the its output so uh that's that algorithm is grounded in the hope or the intuition that the simple answer is the right one it's a formalization of it yeah um it also means like if you would ask the question after how many years would you know sun explode you can say it's more likely the answer is to some power because it's a shorter program yeah and then other well i don't have a good intuition about how different the space of short programs are from the space of large programs like what is the universe where short programs uh like run things uh so as i said the things have to agree with end beats so even if you have you you need to start okay if if you have very short program and they're like uh still some as if it's not perfect with prediction of n bits you have to start errors what are the errors and that gives you the full program that agrees on end beats oh so you don't agree perfectly with the end bits and you store that's like a longer a longer program slightly longer program because it contains these extra bits of errors that's fascinating what's what's your intuition about the the programs that are able to do cool stuff like intelligence and consciousness are they uh perfectly like is is it uh is there if then statements in them so like is there a lot of exceptions that they're storing so um you could imagine if there would be tremendous amount of if statements yeah then they wouldn't be that short in case of neural networks you could imagine that what happens is uh they when you start with an uninitialized neural network uh it stores internally many possibilities how the how the problem can be solved and sgd is kind of magnifying some some some paths which are slightly similar to the correct answer so it's kind of magnifying correct programs and in some sense hdd is a search algorithm in the program space and the program space is represented by uh you know kind of the wiring inside of the neural network and there's like an insane number of ways how that features can be computed let me ask you the high level basic question that's not so basic what is deep learning is there a way you'd like to think of it that is different than like a generic textbook definition the thing that i hinted just a second ago is maybe the uh closest to how i'm thinking these days about um deep learning so now the statement is uh neural networks can represent some programs uh it seems that various modules that we are actually adding up to are like a you know we we want networks to be deep because we we want multiple steps of the computation and and deep learning provides the way to represent space of programs which is searchable and it's searchable with stochastic gradient descent so we have an algorithm to search over a humongous number of programs and gradient descent kind of bubbles up the things that are tend to give correct answers so a neural network with a with fixed weights that's optimized do you think of that as a single program um so there is a work by christopher olach where he so he works on interpretability of neural networks and he was able to uh to identify inside of the neural network for instance a detector of a wheel for a car or the detector of a mask for a car and then he was able to separate them out and assemble them uh together using a simple program uh for the detector for a car detector that's like uh if you think of traditionally defined programs that's like a function within a program that this particular neural network was able to find and you can tear that out just like you can copy and paste from stack overflow that so uh any program is a composition of smaller programs yeah i mean the nice thing about the neural networks is that it allows the things to be more fuzzy than in case of programs in case of programs you have this like a branching this way or that way and the neural networks they they have an easier way to to be somewhere in between or to share things what to use the most beautiful or surprising idea in deep learning in the utilization of these neural networks which by the way for people who are not familiar neural networks is a bunch of uh what would you say it's inspired by the human brain there's neurons there's connection between those neurons there's inputs and there's outputs and there's millions or billions of those neurons and the learning happens uh by adjusting the weights on the edges that connect these neurons thank you for giving definition that i supposed to do it but i guess you have enough empathy to listeners to actually know that that might be useful no that's like so i'm asking plato of like what is the meaning of life he's not going to answer you're being philosophical and deep and quite profound talking about the space of programs which is just very interesting but also for people who are just not familiar with the hell we're talking about when we talk about deep learning anyway sorry what is the most beautiful or surprising idea to you in in um in all the time you've worked at deep learning and you worked on a lot of fascinating projects applications of neural networks it doesn't have to be big and profound it can be a cool trick yeah i mean i'm thinking about the trick but like it's still amusing to me that it works at all yeah that let's say that the extremely simple algorithm stochastic gradient descent which is something that i would be able you know to derive on the piece of paper to high school student uh when put at the ins at the scale of you know thousands of machines actually uh can create the behaviors we which we called kind of human like behaviors so in general any applications to cast a gradient descent to neural networks is is amazing to you so that or is there a particular application in natural language reinforcement learning uh and also would you attribute that success too is it just scale what profound insight can we take from the fact that the thing works for gigantic uh sets of variables i mean the interesting thing is these algorithms they were invented uh decades ago and people actually gave up on the idea yeah and um you know back then they thought that we need profoundly different algorithms and they spent a lot of cycles on very different algorithms and i believe that you know we have seen that various various innovations that say like transformer or or dropout or so they can uh you know pass the help but it's also remarkable to me that this algorithm from 60s or so or i mean you can even say that the gradient descent was invented by leibniz in i guess 18th century or so that actually is the core of learning in the past people are it's almost like a out of the maybe an ego people are saying that it cannot be the case that such a simple algorithm is there you know uh could solve complicated problems so they were in search for the other algorithms and as i'm saying like i believe that actually we are in the game where there is there are actually frankly three levels there is compute there are algorithms and there is data and if we want to build intelligent systems we have to pull all three levers and they are actually multiplicative and it's also interesting so you ask is it only compute people internally they did the studies to determine how much gains they were coming from different levels and so far we have seen that more gains came from compute than algorithms but also we are in the world that in case of compute there is a kind of you know exponential increase in funding and at some point it's impossible to invest more it's impossible to you know invest 10 trillion dollars because we are speaking about that let's say all taxes in u.s uh but you're talking about money there could be innovation in the compute that's that's true as well so i mean they're like a few pieces so one piece is human brain is an incredible super computer [Music] and they're like a it it has 100 trillion parameters or like a if you try to count various quantities in the brain there are like a neurons synapses that small number of neurons there is a lot of synapses yeah it's unclear even how to map synapses to two parameters of neural networks but it's clear that there are many more yeah so it might be the case that our networks are still somewhat small it also might be the case that they are more efficient than brain or less efficient by some by some huge factor i also believe that there will be like a you know at the moment we are at the stage that the these neural networks they require 1000x or like a huge factor of more data than humans do and it will be a matter of there will be algorithms that vastly decrease sample complexity i believe so but the place where we are heading today is dark domains which contains million x more data and even though computers might be 1 000 times slower than humans in learning that's not the problem okay for instance i believe that it should be possible to create super human therapies uh by uh and and then they're like even simple steps of of doing what of of doing it and you know that the core reason is there is just machine will be able to read way more transcripts of therapies and then it should be able to speak simultaneously with many more people and it should be possible to optimize it uh all in parallel and well there's now you're touching on something i deeply care about and think is way harder than we imagined um what's the goal of a therapist what's it called therapies so okay so one goal now this is terrifying to me but there's a lot of people that contemplate suicide suffer from depression and they could significantly be helped with therapy and the idea that an ai algorithm might be in charge of that it's like a life and death task it's uh the stakes are high so one goal for a therapist whether human or ai is to prevent suicide ideation to prevent suicide how do you achieve that so let's see so to be clear i don't think that the current models are good enough for such a task because it requires insane amount of understanding and patty and the models are far from this place but it's but do you think that understanding empathy that signal is in the data um i think there is some signal in the data yes i mean there are plenty of transcripts of conversations and it is possible to it is possible from it to understand personalities it is possible from it to understand uh if conversation is a friendly uh amicable uh antagonistic it is i believe that the you know given the fact that the models that we train now they can they can have they are chameleons that they can have any personality they might turn out to be better in understanding uh personality of other people than anyone else and they feel pathetic to be empathetic yeah interesting uh but i wonder if there's some level of multiple modalities required to be able to be empathetic of the human experience whether language is not enough to understand death to understand fear to understand uh childhood trauma to understand uh wit and humor required when you're dancing with the person who might be depressed or suffering both humor and hope and love and all those kinds of things so there's another underlying question which is self-supervised versus supervised so can you get that from the data by just reading a huge number of transcripts i actually so i think that reading huge number of transcripts is a step one it's like the same way as you cannot learn to dance if just from youtube by watching it you have to actually try it out yourself yeah and so i think that here that's a similar situation i also wouldn't deploy the system in the high-stakes situations right away but kind of see gradually where it goes and obviously initially it would have to go hand with a hand in hand with humans but at the moment we are in the situation that actually there is many more people who actually would like to have a therapy or or speak with with someone then there are therapies out there okay you know i was so so fundamentally i was thinking what are the things that can vastly increase people well-being therapy is one of them i think meditation is other one i guess maybe human connection is a third one and i guess pharmacologically it's also possible maybe direct brain stimulation or something like that but these are pretty much options out there then let's say the way i'm thinking about the agi endeavor is by default that's an endeavor to increase amount of wealth and i believe that we can vastly increase amount of wealth for everyone and simultaneously so i mean they're like two endeavors that make sense to me one is like essentially increase amount of wealth and second one is uh increase overall human well-being and those are coupled together and they they can okay i would say these are different topics one can help another and uh you know therapist is a funny word because i see friendship and love as therapy i mean so therapist broadly defined as just friendship as a friend so like therapist is has a very kind of clinical sense to it but what is human connection you're like uh not to get all camus and dostoyevsky on you but you know life is suffering and we draw we seek connection with other humans as we desperately try to make sense of this world in the deep overwhelming loneliness that we feel inside so i think connection has to do with understanding and i think that almost like a lack of understanding causes suffering if you speak with someone and you do you feel ignored that actually causes pain if you are feeling deeply understood that actually they they might not even tell you what to do in life but like a pure understanding or just being heard understanding is a kind of it's a lot you know just being heard feel like you're being heard like somehow that's uh alleviation temporarily of the loneliness that if somebody knows you're here with their body language with the way they are with the way they look at you with the way they talk you feel less alone for a brief moment yeah very very much agree so i thought in the past about uh somewhat similar question to yours which is what is love uh rather what is connection yes and um and obviously i think about these things from ai perspective what would it mean um so i said that the you know intelligence has to do with some compression which is more or less like i can say almost understanding of what is going around it seems to me that uh other aspect is there seem to be reward functions and you can have a you know reward for uh food for maybe human connection for uh let's say warmth uh sex and so on and um and it turns out that the various people might be optimizing slightly different reward functions they essentially might care about different things and um in case of love at least the love between two people you can say that the um you know boundary between people dissolves to such extent that they end up optimizing each other reward functions yeah oh that's interesting um the success of each other yeah in some sense i would say love means uh helping others to optimize their uh reward functions not your reward functions not the things that you think are important but the things that the person cares about you try to help them to optimize it so love is uh if you think of two reward functions you just it's a condition yeah you combine them together yeah pretty much maybe like with a weight and it depends like the dynamic of the relationship yeah i mean you could imagine that if you are fully uh optimizing someone's reward function without yours then yeah then maybe are creating code dependency or something like that yeah i'm not sure what's the appropriate weight but the interesting thing is i even i even think that the individual person we ourselves we are actually less of a unified insight so for instance if you look at the donut on the one level you might think oh this like it looks tasty i would like to eat it on another level you might tell yourself i shouldn't be doing it because i want to gain muscles so and you know you might do it regardless kind of against yourself so it seems that even within ourselves they're almost like a kind of intertwined personas and i believe that the self-love means that the love between all these persons which also means being able to love love yourself when we are angry or stressed or so combining all those reward functions of the different selves you have yeah and accepting that they are there okay you know often people they have a negative self-talk or they say i don't like when i'm angry and like i try to imagine try to imagine if there would be like a small baby alex like a five years old who's angry angry and then you're like you shouldn't be angry like stop being angry yeah but like instead actually you want the legs to come over give him a hug and he's like i say it's fine okay you can't be angry as long as you want yeah then he would stop or or maybe not or maybe not but you cannot expect it even yeah but still that doesn't explain the why of love like why is love part of the human condition why is it useful to combine the reward functions it seems like that doesn't i mean i don't think reinforcement learning frameworks can give us answers to why even even the hudder framework has an objective function that's static so we came to existence as a consequence of evolutionary process and in some sense the purpose of evolution is survival and then the this complicated optimization objective baked into us let's say compression which might help us operate in the real world and it bake into us various reward functions yeah and then to be clear at the moment we are operating in the regime which is somewhat out of distribution where the event evolution optimized us it's almost like love is a consequence of cooperation that we've discovered is useful correct in some way it's even the case if you i just love the idea that love is like the out of distribution or it's not out of distribution it's like as you that it evolved for cooperation yes and i believe that the cop like a in some sense cooperation ends up helping each of us individually so it makes sense evolutionary and there is a in some sense and you know love means there is this dissolution of boundaries that you have a shared reward function and we evolve to actually identify ourselves with larger groups so we we can identify ourselves you know with a family we can identify ourselves with a country to such an extent that people are willing to give away their life for country [Music] so there is we are wired actually even uh for love and at the moment i guess the maybe it would be somewhat more beneficial if you will if we would identify ourselves with all the humanity as a whole so so you can clearly see when people travel around the world when they run into person from the same country they say oh which ctr and all this like all of a sudden they find all these similarities they they they find some they befriend those folks earlier than others so there is like a sense some sense of the belonging and i would say i think it would be overall good thing to the word for people to move towards i think it's even called open individualism and move toward the mindset of a larger and larger groups so the challenge there that's a beautiful vision and i share it to expand that circle of empathy that circle of love towards the entirety of humanity but then you start to ask well where do you draw the line because why not expand it to other conscious beings and then at the finally for our discussion something i think about is why not expand it to ai systems like we we start respecting each other when the other the person the entity on the other side has the capacity to suffer because then we develop a capacity to sort of empathize and so i could see ai systems that are interacting with humans more and more having conscious like displays so like they display consciousness through language and through other means and so then the question is like well is that consciousness because they're acting conscious and so you know the reason we don't like torturing animals is because they look like they're suffering when they're tortured and if ai looks like it's suffering when it's tortured how is that not requiring of the same kind of empathy from us and respect and rights that animals do and other humans do i think it requires empathy as well i mean i would like i guess us or humanity or so make a progress in understanding what consciousness is because i don't want just to be speaking about that the philosophy but rather actually make a scientific uh to have a like a you know there was a time that people thought that there is a force of life and the things that have this force they are alive and i think that there is actually a path to understand exactly what consciousness is and um in some sense it might require essentially putting probes inside of a human brain what neuralink does so the goal there i mean there's several things with consciousness that make it a real discipline which is one is rigorous measurement of consciousness and then the other is the engineering of consciousness which may or may not be related i mean you could also run into trouble like for example in the united states for the department d.o.t department of transportation and a lot of different places put a value on human life i think dot's uh values nine million dollars per person sort of in that same way you can get into trouble if you put a number on how conscious a being is because then you can start making policy if a cow is uh 0.1 or like um 10 as conscious as a human then you can start making calculations and might get you into trouble but then again that might be a very good way to do it i would like uh to move to that place that actually we have scientific understanding what consciousness is yeah and then we'll be able to actually assign value and i believe that there is even the path for the experimentation in it so uh you know we said that you know you could put the probes inside of the brain there is actually few other things that you could do with devices like neuralink so you could imagine that the way even to measure if ai system is conscious is by literally just plugging into the brain and i mean that that seems that's kind of easy but the plugging into the brain and asking person if they feel that their consciousness expanded this direction of course has some issues you can say you know if someone takes a psychedelic drug they might feel that their consciousness expanded even though that drug itself is not conscious right so like you can't fully trust the self-report of a person saying their their consciousness is expanded or not let me ask you a little bit about psychedelics because uh there's been a lot of excellent research on uh different psychedelics psilocybin mdma yeah even dmt drugs in general marijuana too uh what do you think psychedelics do to the human mind it seems they take the human mind to some interesting places is that just a little uh hack a visual hack or is there some profound expansion of the mind so let's see i i don't believe in magic i believe in that i believe in in science in in causality still let's say and then as i said like i think that the brain that the our subjective experience of reality is uh we live in the simulation run by our brain and the simulation that our brain runs they can be very pleasant or very hellish drugs they are changing some hyper parameters of the simulation it is possible thanks to change of these hyper parameters to actually look back on your experience and even see that the given things that we took for granted they are changeable so they allow to have a amazing perspective there is also for instance the fact that after dmt people can see the full movie inside of their head gives me further belief that the brain can generate that full movie that the brain is actually learning the model of reality to such extent that it tries to predict what's going to happen next yeah very high resolution so it can replay realities actually extremely high resolution and it's also kind of interesting to me that somehow there seems to be some similarity between these uh drugs and meditation itself and i actually started even these days to think about meditation as a psychedelic and do you practice meditation i i practice meditation i mean i once few times on the retreats and it feels after like after second or third day of meditation there is a there is almost like a sense of you know tripping what does the meditation retreat entail so i mean you you wake up early in the morning and you meditate for extended period of time and alone yeah so it's optimized even though there are other people it's optimized for isolation so you don't speak with anyone you don't actually look into other people's eyes and you know you sit on the chair and say the passage meditation tells you uh to focus on the breath so you try to put all the all attention into breathing and breathing in and breathing out and the crazy thing is that as you focus attention like that after some time their stamps starts coming back like some memories that you completely forgotten it almost feels like um that you have a mailbox and then you you know you are just like a archiving email one by one and at some point at some point there is like a amazing feeling of getting to mailbox zero zero emails and uh it's very pleasant it's it's kind of it's it's it's crazy to me that that once you resolve these inner stories or like inner traumas then once there is nothing uh left the default state of human mind is extremely peaceful and happy extreme like some sense it it feels that it feels at least to me in the way how when i was a child that i can look at any object and it's very beautiful i have a lot of curiosity about the simple things and that's where usually meditation takes me are you what are you experiencing are you just taking in simple sensory information and they're just enjoying the rawness of that sensory information so there's no there's no memories all that kind of stuff you're just enjoying being yeah pretty much i mean still there is a there it's it's thoughts are slowing down sometimes they pop up but it's also somehow the extended meditation takes you to the space that they are way more friendly you know way more positive um there is also this uh this thing that we've actually it almost feels that the it almost feels that the we are constantly getting a little bit of a reward function and we are just spreading this reward function on various activities but if you stay still for extended period of time it kind of accumulates accumulates accumulates and there is a there is a sense there is a sense that at some point it passes some threshold and it feels as drop is falling into kind of ocean of love and bliss and that's like a this is like a very pleasant and as i'm saying okay that corresponds to the subjective experience some people uh i guess in spiritual community they describe it that that's the reality and i would say i believe that they're like all sorts of subjective experience that one can have and i believe that for instance meditation might take you to the subjective experiences which are very pleasant collaborative and i would like a word to move toward a more collaborative uh place yeah i would say that's very pleasant that i enjoy doing stuff like that i i i wonder how that maps to your uh mathematical model of love with the the reward function combining a bunch of things it seems like our life then is we're just we have this reward function and we're accumulating a bunch of stuff in it with weights it's like um like multi-objective and what meditation is is you just remove them remove them until the weight on one or just a few is is very high and that's where the pleasure comes from yeah so something similar how i'm thinking about this so i told you that there is like a there is a story of who you are and i think almost about it as a you know text prepended to gpt yeah and some people refer to it as ego okay it's like a story who who you are okay so ego is the prompt for gpt three gpg yes yes and that's description of you and then with meditation you can get to the point that actually you experience things without the prompt and you experience things like as they are you are not biased over the description how they supposed to be uh that's very pleasant and then with respect to the reward function uh it's possible to get to the point that the there is dissolution of self and therefore you can say that they are you you're having a you're or like your brain attempts to simulate the reward function of everyone else or like everything that's there is this like a love which feels like a oneness with everything and that's also you know very beautiful very pleasant at some point you might have a lot of altruistic thoughts during that moment and then the self uh always comes back how would you recommend if somebody is interested in meditation like a big thing to take on as a project would you recommend a meditation retreat how many days what kind of thing would you recommend i think that actually retreat is the way to go and it almost feels that as i said like a meditation is a psychedelic but when you take it in the small dose you might barely feel it once you get the high dose actually you're gonna feel it um so even cold turkey if you haven't really seriously meditated for a prolonged period of time just go to a retreat yeah how many days how many days start the weekend one weekend so like two three days and it's like it's interesting that first or second day it's hard and at some point it becomes easy there's a lot of seconds in a day how hard is the meditation retreat just sitting there in a chair so the thing is actually it literally just depends on your uh on death your own framing like if you are in the mindset that you are waiting for it to be over or you are waiting for nirvana to happen it will be very unpleasant yeah and in some sense even the difficulty it's not even in the lack of being able to speak with others like you are sitting there your legs will hurt from sitting in terms of like the practical things do you experience kind of discomfort like physical discomfort of just sitting like your your butt being numb your legs being sore all that kind of stuff yes you experience it and then the they teach you to observe it rather and it's like a the crazy thing is you at first might have a feeling toward trying to escape it yeah and that becomes very apparent that that's extremely unpleasant and then you just just observe it and at some point it it just becomes uh it just is it's like a i remember with ilya told me some time ago that uh you know he takes a cold shower and his mindset of taking a court cold shower was to embrace suffering yeah excellent i do the same there's the art style yes my style i like this so my style is actually i also sometimes take cold showers it is purely observing how the water goes through my body like a purely being present not trying to escape from there yeah and i would say then it actually becomes pleasant it's not like ah well that that's interesting um i i'm also that mean that's that's the way to deal with anything really difficult especially in the physical space is to observe it to say it's pleasant it's a i would use a different word your uh you're accepting of the full beauty of reality i would say because say pleasant but yeah i mean in some sense it is pleasant that's the only way to deal with a cold shower is to to become an observer and to find joy in it same with like really difficult physical uh exercise or like running for a really long time endurance events just anytime you're exhausted any kind of pain i think the only way to survive it is not to resist it just to observe it you mentioned ilya elias discover he's very he's our chief scientist but also he's very close friend of mine he co-founded open air with you i've spoken with him a few times he's brilliant i really enjoy talking to him his mind just like yours works in fascinating ways now both of you are not able to define deep learning simply uh what's it like having him as somebody you have technical discussions with on in space machine learning deep learning ai but also life what's it like when these two uh agents get into a self-play situation in in a room what's it like collaborating with him so i believe that we have extreme uh respect to each other so um i mean i love ilia's insight both like uh i guess about consciousness uh life ai but uh in terms of the it's interesting to me because you're a brilliant uh thinker in the space of machine learning like intuition like digging deep in what works what doesn't why it works why it doesn't and so is ilia i'm wondering if there's interesting deep discussions you've had with him in the past or disagreements that were very productive so i can say i also understood over the time where are my strengths so obviously we have plenty of ai discussions and um and you know i myself have plenty of ideas but like i consider ilya one of the most prolific ai scientists in the entire world and i think that um i realized that maybe my super skill is being able to bring people to collaborate together that i have some level of empathy that is unique in ai world and that might come you know from either meditation psychedelics or let's say i read just hundreds of books on this topic so and i also went through a journey of you know i develop all sorts of algorithms so i think that maybe i can that's my super human skill uh ilia is one of the best ai scientists but then i'm pretty good in assembling teams and i'm also not holding two people like i'm growing people and then people become managers that open yeah there's room any of them like a research manager so you you find you find places where you're excellent and and he finds like his his deep scientific insights is where he is and you find ways you can the puzzle pieces fit together correct okay you know ultimately for instance let's say ilia he doesn't manage people uh that's not what he likes or so um i i like i like hanging out with people by default i'm an extrovert and i care about people oh interesting okay okay cool so that that fits perfectly together but i i mean uh i also just like your intuition about various problems in machine learning he's definitely one i really enjoy i remember talking to him about something i was struggling with which is coming up with a good model for pedestrians for human beings across the street in the context of autonomous vehicles and he immediately started to like formulate a framework within which you can evolve a model for pedestrians like through self-play all that kind of mechanisms the depth of thought on a particular problem especially problems he doesn't know anything about is fascinating to watch it makes you realize like um yeah the the limits of the that the human intellect might be limitless or it's just impressive to see a descent on the vape come up with clever ideas yeah i mean so even in the space of deep learning when you look at various people there are people you know who invented some breakthroughs once but there are very few people who did it multiple times and you can think if someone invented it once that might be just a shared luck and if someone invented it multiple times you know if a probability of inventing it once is one over a million then probability of inventing it twice or three times would be one over a million square or to the power of three which which would be just impossible so it literally means that it's it's given that uh it's not the luck yeah and ilea is one of these few people who um who have uh a lot of these inventions in his arsenal it also feels that the now for instance if you think about folks like gauss or euler and you know at first they read a lot of books and then they did thinking and then they figure out math and that's how it feels with ilya yeah you know at first he read stuff and then like he spent his thinking cycles and that's a really good way to put it when i talk to him [Music] i i see thinking he's actually thinking like he makes me realize that there's like deep thinking that the human mind can do like most of us are not thinking deeply like you really have to put a lot of effort to think deeply like i have to really put myself in a place where i think deeply about a problem it takes a lot of effort it's like a it's like an airplane taking off or something you have to achieve deep focus he he's just uh he's what is it his brain is like a vertical takeoff in terms of airplane analogy so it's interesting but it i mean cal newport talks about this as ideas of deep work it's you know most of us don't work much at all in terms of like like deeply think about particular problems whether it's math engineering all that kind of stuff you want to go to that place often and that's real hard work and some of us are better than others at that so i think that the big piece has to do with actually even engineering your environment such that it's conducive to that yeah so um see both ilia and i uh on the frequent basis we kind of disconnect ourselves from the world in order to be able to do extensive amount of thinking yes so ilia usually he just leaves ipad at hand he loves his ipad and for me i'm even sometimes you know just going for a few days to different location to airbnb i'm turning off my phone and there is no access to me yeah and that's extremely important for me to be able to actually just formulate new thoughts to do deep work rather than to be reactive and the the older i am the more of these like random tasks are at hand before i go on to that uh thread let me return to our friend gpt let me ask you another ridiculously big question can you give an overview of what gpt 3 is or like you say in your twitter bio gpt n plus one how it works and why it works so um gpt 3 is a humongous neural network and let's assume that we know what is neural network okay by the definition and it is trained on the entire internet and just to predict next word so let's say it sees part of the uh article and it the only task that it has at hand it is to say what would be the next word uh what would be the next word and it becomes uh really exceptional at the task of figuring out what's the next word so you might ask why would this be an important task why would it be important to predict what's the next word and it turns out that a lot of problems uh can be formulated uh as a text completion problem so gpt is purely uh learning to complete the text and you could imagine for instance if you are asking a question who is a president of united states then gpt can give you an answer to it it turns out that many more things can be formulated this way you can format text in the way that you have sentence in english you make it even look like a some content of a website uh elsewhere which would be teaching people how to translate things between languages so it would be en colon text in english fr colon and then you uh and then you ask people and then you ask model to to continue and it turns out that the such a model is predicting translation from english to french the crazy thing is that this model can be used for way more sophisticated tasks so you can format text such that it looks like a conversation between two people and that might be a conversation between you and elon musk and because the model read all the texts about elon musk it will be able to predict elon musk words as it would be elon musk it will speak about colonization of mars about sustainable future and so on and it's also possible to to even give arbitrary personality to the model you can say here is a conversation with a friendly ai bot and the model uh will complete the text as a friendly ai bot so i mean how do i express how amazing this is so just to clarify a conversation generating a conversation between me and elon musk it wouldn't just generate good examples of what elon would say it would get the syntax all correct so like interview style you would say like elon colon and lex con like it it's not just like uh inklings of semantic correctness it's like the whole thing grammatical syntactic semantic it's just really really impressive uh generalization yeah i mean i also want to you know provide some caveats so it can generate few paragraphs of coherent text but as you go to uh longer pieces it actually goes off the rails okay if you would uh try to write a book it won't work out uh this way what way does it go off the rails by the way is there interesting ways in which it goes off the rails like what falls apart first so the model is trained on the all the existing data that is out there which means that it is not trained on its own mistakes so for instance if it would make a mistake then uh i kept so to give give you an example so let's say i have a conversation with a model pretending that is elon musk and then i start putting some i'm start actually making up things which are not factual um i would say like twitter but i gotcha sorry yeah um okay i don't know i would say that elon is my wife and the model will just keep on carrying it on and as if it's true yes and in some sense if you would have a normal conversation with elon he would be what the fuck yeah there would be some feedback between so the the model is trained on things that humans have written but through the generation process there's no human in the loop feedback correct that's fascinating makes sense so it's magnified it's like the errors get magnified and magnified right and it's a it's also interesting i mean first of all humans have the same problem it's just that we uh we make fewer errors and magnify the errors slower i think that actually what happens with humans is if you have a wrong belief about the world as a kid then very quickly you will learn that it's not correct because you are grounded in reality and you are learning from your new experience yes but do you think the model can correct itself too it through the power of the representation and so the absence of elon musk being your wife information on the internet want to correct itself there won't be examples like that so the errors would be subtle at first saddle at first and in some sense you can also say that the data that is not out there is the data which would represent how the human learns that's an a and and maybe model would be trained on such a data then it would be better off how intelligent is gpt 3 do you think like when you think about the nature of intelligence it seems exceptionally impressive but then if you think about the big agi problem is this footsteps along the way to agi so let's see seems that intelligence itself is there are multiple axis of it and i would expect that the the systems that we are building they may end up being super human on some axis and sub human on some other axis it would be surprising to me on all axis simultaneously they would become superhuman of course people ask this question is gpt a spaceship that that would take us to moon or are we putting a building a ladder to heaven that we are just building bigger and bigger ladder and we don't know in some sense uh which one of these two which one is better i'm trying to i like stairway to heaven that's a good song so i'm not exactly sure which one is better but you're saying like the the spaceship to the moon is actually effective correct so people who criticize gpt yeah they say jarga is just building a taller a ladder and it will never reach the moon and at the moment i would say the way i'm thinking is this like a scientific question and i'm also in heart i'm a builder creator and like i'm thinking let's try out let's see how far it goes and so far we see constantly that there is a progress yeah so what do you think gpt4 gpt5 gpt n plus one will uh there'll be a phase shift like a transition to a to a place where we'll be truly surprised then again like gpt3 is already very like truly surprising the people that criticize gpg3 as it's there as a what is it ladder to heaven i think too quickly get accustomed to how impressive it is that the prediction of the next word can achieve such depth of semantics accuracy of syntax grammar and semantics um do you do you think gpt four and five and six will continue to surprise us i mean definitely there will be more impressive models there is a question of course if there will be a phase shift and the also even the way i'm thinking about the about these models is that when we build these models you know we see some level of the capabilities but we don't even fully understand everything that the model can do and actually one of the best things to do is to allow other people to probe the model to even see what is possible hence the using gpg as an api and opening it up to the world yeah i mean so when i'm thinking from perspective of there like a obviously various people are that have concerns about agi including myself and then when i'm thinking from perspective what's the strategy even to deploy these things to the world the the one strategy that i have seen many times working is the iterative deployment that you deploy um slightly better versions and you allow other people to criticize you so you actually are tried out you see where are their fundamental issues and it's almost you don't want to be in that situation that you are holding into powerful system and there's like a huge overhang then you deploy it and it might have a random chaotic impact on the world so you actually want to be in the situation that they are gradually deploying systems i asked this question of ilio let me ask you you this question i've been reading a lot about stalin and power if you're in possession of a system that's like agi that's exceptionally powerful do you think your character integrity might become corrupted like famously power corrupts and absolute power corrupts absolutely so i believe that you want at some point to work toward distributing the power i think that you want to be in the situation that actually agi is not controlled by a small number of people but essentially by a larger collective so the thing is that requires a george washington style move in the ascent to power there's always a moment when somebody gets a lot of power and they have to have the integrity and uh the moral compass to give away that power that humans have been good and bad throughout history at this particular step and i wonder i wonder we like blind ourselves in uh for example between nations a race uh towards uh yeah ai race between nations we might blind ourselves and justify to ourselves the development of ai without distributing the power because we want to defend ourselves against china against russia that kind of that kind of logic and i wonder how we um how we design governance mechanisms that um prevent us from becoming power hungry and in the process destroying ourselves so let's see i have been thinking about this topic quite a bit but i also want to admit that uh once again i actually want to rely way more on sam outman on it hero than a heroed an excellent block on how even to distribute wealth and his proper he proposed in his block to tax equity of the companies rather than profit and to distribute it and this is this is an example of uh washington move i guess i personally have insane trust in some he already spent plenty of money running a universal basic income project that like gives me i guess maybe some level of trust to him but i also i guess love him as a friend yeah i wonder because we're sort of summoning a new set of technologies i wonder if we'll be cognizant like you're describing the process of open ai but it could also be at other places like in the us government right both china and the us are now full steam ahead on autonomous weapons systems development and that's really worrying to me because in the framework of something being a national security danger or military danger you can do a lot of pretty dark things that blind our moral compass and i think ai will be one of those things in some sense the the mission and the work you're doing at openai is like the counterbalance to that so you want to have more open ai and less autonomous weapon systems i i i like these statements like to be clear like this interesting and i'm thinking about it myself but uh this is a place that i i okay i put my trust actually in some hence because it's extremely hard for me to reason about it yeah i mean one important statement to make is um it's good to think about this yeah no question about right no question even like low-level quote-unquote engineer like there's such a i remember i i programmed a car uh our rc car they went really fast like 30 40 miles an hour and i remember i was like sleep deprived so i programmed it pretty crappily and it like uh the the code froze so it's doing some basic computer vision and it's going around on track but it's going full speed and uh there's a bug in the code that uh the car just went it didn't turn it went straight full speed and smashed into the wall i remember thinking the seriousness with which you need to approach the design of artificial intelligence systems and the programming of artificial intelligence systems is high because the consequences are high like that little car smashing it to the wall for some reason i immediately thought of like an algorithm that controls nuclear weapons having the same kind of bug and so like the lowest level engineer and the ceo of a company all need to have the seriousness in approaching this problem and thinking about the worst case consequences so i think that is true i mean the what i also recognize in myself and others even asking this question is that it evokes a lot of fear and fear itself ends up being actually quite debilitating the place where i arrived at the moment might sound cheesy or so but it's almost to build things out of love rather than fear yeah i can focus on how i can you know maximize the value how the systems that i'm building might be uh useful i'm not saying that the fear doesn't exist out there and like it totally makes sense to minimize it but i don't want to be working because uh i'm scared i want to be working out of passion out of curiosity out of the you know looking forward for the positive future with uh the definition of love arising from a rigorous practice of empathy so not just like your own conception of what is good for the world but uh always listening to others correct like at the love where i'm considering reward functions of others others to infil limit to infinity is like a sum like one to n where n is uh seven billion or whatever it is not not projecting my reward functions on others yeah exactly okay can we just take a step back to something else super cool which is uh opening up codex can you give an overview of what open-air codecs and github co-pilot is how it works and why the hell it works so well so with gpd3 we noticed that the system um you know that system training all the language out there started having some rudimentary coding capabilities so we're able to ask it you know to implement addition function between two numbers and indeed it can write python or javascript code for that and then we thought um we might as well just go full steam ahead and try to create a system that is actually good at what we are doing every day ourselves which is programming we optimize models for proficiency in coding we actually even created models that both have a comprehension of language and code and codex is api for these models so it's first pre-trained on language and then i don't know if you can say fine-tuned because there's a lot of code but it's language and code it's language and code it's also optimized for various things like let's say low latency and so on codex is the api that's similar to gpd3 we expect that there will be proliferation of the potential products that can use coding capabilities and i can i can speak about it in a second compiled is the first product and developed by github so as we're building uh models we wanted to make sure that these models are useful and we work together with github on building the first product co-pilot is actually as you code it suggests you code completions and we have seen in the past they're like a various tools that can suggest how to like a few characters of the code or the line of code the the thing about copilot is it can generate 10 lines of code you it's often the way how it works is you often write in the comment what you want to happen because people in comments they describe what happens next so um these days when i code instead of going to google to search for the appropriate code to solve my problem i say oh for this array could you smooth it and then you know it imports some appropriate libraries and say it uses numpy convolution or so i that i was not even aware that exists and it does the appropriate thing um so you you write a comment maybe the header of a function and it completes the function of course you don't know what is the space of all the possible small programs it can generate what are the failure cases how many edge cases how many subtle errors there are how many big errors there are it's hard to know but the fact that it works at all on in a large number of cases is incredible it's like a it's a kind of search engine into code that's been written on the internet correct so for instance when you search things online then usually you get to the some particular case like if you go to stack overflow people describe that one particular situation uh and then they seek for a solution but in case of uh co-pilot it's aware of your entire context and in contexts oh these are the libraries that they are using that's the set of the variables that is initialized and on the spot it can actually tell you what to do so the interesting thing is and we think that the copilot is one possible product using codex but there is a place for many more so internally we tried out you know to create other fun products so it turns out that a lot of tools out there let's say google calendar or microsoft word or so they all have uh internal api to build plugins around them so there is a way in the sophisticated way to control calendar or microsoft word today if you want if you want more complicated behaviors from these programs you have to add a new button for every behavior but it is possible to use codex and tell for instance to calendar could you schedule an appointment with blacks next week after 2 pm and either writes corresponding piece of code and that's the thing that actually you want so interesting so what you figure out is there's a lot of programs with which you can interact through code and so there you can generate that code from natural language that's fascinating and that's somewhat like also closest to uh what was the promise of siri or alexa yeah so previously all these behaviors they were had hard coded yeah and it seems that codex on the fly can pick up the api of let's say given software yeah and then it can turn the language into use of this api without hard coding you can find it can translate to machine language correct it to uh so for example this would be really exciting for me like for um adobe products like photoshop uh which is the i think actionscript i think there's a scripting language that communicates with them same with premiere and you could imagine that that allows event to do coding by voice on your phone so for instance in the past okay as of today i'm not editing word documents on my phone because it's just the keyboard is too small but if i would be able to tell to my phone you know uh make the header large and then move the paragraphs around and it does actually what i want so i can tell you one more cool thing or even how i'm thinking about codex so if you look actually at the evolution of of computers we started with very primitive interfaces which is a punch card and punch card essentially you make a holes in the in the plastic card to indicate zeros and ones and during that time there was a small number of specialists who were able to use computers and by the way people even suspected that there is no need for many more people to use computers but then we moved from punch cards to at first assembly then c and these programming languages they were slightly higher level they allowed many more people to code and they also led to more of a proliferation of technology and you know further on there was a jump to say from c plus plus to java and python and every time it has happened more people are able to code and we build more technology and it's even you know hard to imagine now if someone will tell you that you should write code in assembly instead of let's say python or or or java or javascript and codex is yet another step toward kind of bringing computers closer to humans such that you communicate with a computer with your own language rather than with a specialized language and i think that it will lead to an increase of number of people who can code yeah and then and the kind of technologies that those people will create is like it's innumerable it could you know it could be a huge number of technologies we're not predicting at all because that's less and less requirement of uh having a technical mind a programming mind you're not opening it to the world of um other kinds of minds creative minds artistic minds all that kind of stuff i would like for instance biologists who work on dna to be able to program and not to need to spend a lot of time uh learning it and i i believe that's a good thing to the word and i would actually add out that so at the moment i'm a managing codex team and also language team and i believe that there is like a plenty of brilliant people out there and they should apply oh okay yeah awesome so what's the language in the codexes so those are kind of they're overlapping teams so it's like gpt the raw language and then the codex is like applied to programming correct and they are quite intertwined there are many more teams involved making these uh models extremely efficient and deployable for instance there are people who are working to you know make our data centers uh amazing or there are people who work on pro putting these models into production or uh or even pushing it at the very limit of the scale so all aspects from from the infrastructure to the actual machine learning so i'm just saying that multiple teams while the and the team working on codex and language uh i guess i'm i'm directly managing them i would like i would love to hire yeah if you're interested in machine learning this is probably one of the most exciting uh problems and like systems to be working on because it's actually it's it's pretty cool like what what uh the program synthesis like generating of programs is very interesting very interesting problem that has echoes of reasoning and intelligence in it it and i think there's a lot of fundamental questions that you might be able to sneak sneak up to by generating programs yeah the one more exciting thing about the programs is that so i said that the um you know the in case of language that one of the troubles is even evaluating language so when the things are made up you you need somehow either a human to say that this doesn't make sense or so in case of program there is one extra level that we can actually execute programs and see what they evaluate to so that process might be somewhat more automated in in order to improve the uh qualities of generations and that's not saying so like the wow that's really interesting so for the language that you know the simulation to actually execute it as a human mind yeah for programs there is a there is a computer on which you can evaluate it wow that's a brilliant little insight that the thing compiles and runs that's first and second you can evaluate on a like do automated unit testing and in some sense it seems to me that we will be able to make a tremendous progress you know we are in the paradigm that there is way more data and there is like a transcription of millions of uh of uh software engineers yeah yeah so i mean you just me because i was going to ask you about reliability the thing about programs is you don't know if they're going to like a program that's controlling a nuclear power plant has to be very reliable so i i wouldn't start with controlling nuclear power plant can i be one day but that that's not actually that's not on the current roadmap that's not that's step one and you know it's the russian thing you just want to go to the most powerful destructive thing right away run by javascript but i got you so it's a lower impact but nevertheless what you're making me realize it is possible to achieve some levels of reliability by doing testing and i thought you could imagine that them you know maybe there are ways for a model to write even code for testing itself and so on and there exists a ways to create the feedback loops that the model could keep on improving by writing programs that generate tests for the instance for instance and that's how we get consciousness because it's meta compression that's what you're going to write that's the comment that's the prompt that generates consciousness compressor of compressors you just write that do you think the code that generates consciousness would be simple so let's see i mean ultimately the core idea behind will be simple but there will be also decent amount of engineering involved like in some sense it seems that you know spreading these models on many machines and it's not that trivial yeah and we find all sorts of innovations that make our models more efficient i believe that first models that i guess are conscious are like a truly intelligent they will have all sorts of tricks but then again there's uh which is certain argument that maybe the tricks are temporary thing yeah they might be temporary things and in some sense it's also even important to um to know that even the cost of a trick so sometimes people are eager to put the trick while forgetting that there is a cost of maintenance or like a long-term cost long-term cost or maintenance or maybe even flexibility of code to actually implement new ideas so even if you have something that gives you 2x but it requires you know 1000 lines of code i'm not sure if it's actually worth it so in some sense you know if it's five lines of code and 2x i would take it and and we we we see many of this but also you know that requires some level of i guess lack of attachment to code that we are willing to remove it yeah so you led the open ai robotics team can you give an overview of of the cool things you're able to accomplish what are you most proud of so when we started robotics we knew that actually reinforcement learning works and it is possible to solve very complicated problems like for instance alphago is an evidence that it is possible to to build superhuman and gold players dota 2 is a an evidence that is possible to build superhuman uh agents playing dota so i asked myself a question you know what about robots out there could we train machines to solve arbitrary tasks in the physical world our approach was i guess let's pick a complicated problem that if we would solve it that means that we made some uh significant progress in the domain and then we went after the problem so um we noticed that actually the robots out there they are kind of at the moment optimized per task so you can have a robot that it's like if you have a robot opening a battle it's very likely that the end factor is a battle opener and and in some sense that's a hack to be able to solve a task which makes any task easier and um ask myself so what would be a robot that can actually solve many tasks yeah and we conclude that that like a human hands have such a quality that indeed they are you know you have five kind of tiny arms attached individually they can manipulate pretty broad spectrum of objects so we went after a single hand like a trying to solve rubik's cube single-handed we picked this task because we thought that there is no way to harcode it and it's also we picked the robot on which it would be hard to hardcode it and we went after the solution such that it could generalize to other problems and just to clarify it's one robotic hand solving the rubik's cube the hard part isn't the solution to the rubik's cube is the manipulation of the uh of like having it not fall out of the hand having it use the uh five baby arms to uh what is it like rotate different parts of the rubik's cube to achieve the solution correct yeah so what uh what was the hardest part about that what was the approach taken there what are you most proud of obviously we have like a strong belief in reinforcement learning and uh you know one path it is to do reinforcement learning the real world other path is to the simulation in some sense the tricky part about the real world is at the moment our models they require a lot of data there is essentially no data and i did we decided to go through the path of the simulation and in simulation you can have infinite amount of data the tricky part is the fidelity of the simulation and also can you in simulation represent everything that you represent otherwise in the real world and you know it turned out that uh that you know because there is lack of fidelity it is possible to that what we what we arrived at is training a model that doesn't solve one simulation but it actually solves the entire range of simulations which uh vary uh in terms of like uh what's the exactly the friction of that cube or the weight or so and the single ai that can solve all of them ends up working well with the reality how do you generate the different simulations so you know there's plenty of parameters out there we just pick them randomly and and in simulation model just goes for thousands of years and keeps on solving rubik's cube in each of them and the thing is the neural network that we used it has a memory and as it presses for instance the side of the of the cube it can sense oh that's actually this side was uh difficult to press i should press it stronger and throughout this process kind of learns even how to how to solve this particular instance of the rubik's cube back even mass it's kind of like a you know sometimes when you go to a gym and after after bench press you try to lift the and you kind of forgot uh and and your hand goes like yeah right away because kind of you got this to maybe different weight yeah and it takes a second to adjust yeah and this kind of of a memory that model gained through the process of interacting with the cube in the simulation i appreciate you speaking to the audience with the bench press all the bros in the audience probably working out right now there's probably somebody listening to this actually doing bench press so maybe uh put the bar down and pick up the water bottle and you'll know exactly what uh what check is talking about okay so what uh what was the hardest part of getting the whole thing to work so the hardest part is at the moment when it comes to a physical world when it comes to robots they require maintenance it's hard to replicate a million times it's it's also it's hard to replay things exactly i remember this situation that one guy at our company he had like a model that performs way better than other models in solving rubik's cube and you know we kind of didn't know what's going on why it's that and it turned out that you know he was running it from his laptop that had better cpu or uh or better or maybe local gpu as well and uh because of that there was less of a latency and the model was the same and that actually made solving rubik's cube more reliable so in some sense there might be some saddlebacks like that when it comes to running things in the real world even hinting on that you could imagine that the initial models you would like to have models which are insanely huge neural networks and you would like to give them even more time for thinking and when you have these real-time systems then you might be constrained actually by the amount of latency and ultimately i would like to build the system that it is worth for you to wait five minutes because it gives you the answer that you are willing to wait for five minutes so latency is a very unpleasant constraint underwish to operate correct and also there is actually one more thing which is tricky about robots there is actually no not much data so the data that i'm speaking about would be a data of first person experience from the robot and like a gigabytes of data like that if we would have gigabytes of data like that of robot solving various problems it would be very easy to make a progress on robotics and you can see that in case of text or code there is a lot of data like a first person perspective data on the writing code yeah so you had this you mentioned this really interesting idea that if you were to build like a successful robotics company so open as mission is much bigger than robotics this is one of the one of the things you've worked on but if it was a robotics company they you wouldn't so quickly dismiss supervised learning i correct that you would build a robot that was perhaps one like um an empty shell like dumb and they would operate under tele operation so you would invest that's just one way to do it invest in human super like direct human control of the robots as it's learning and over time add more and more automation that's correct so let's say that's how i would build a robotics company today if i would be building a robotics company which is you know spent 10 million dollars or so recording human trajectories controlling a robot after you find a thing that the robot should be doing that there's a market fit for like that you can make a lot of money with that product correct correct yeah so i would record data and then i would essentially train supervised learning model on it that might be the path today long term i think that actually what is needed is to train powerful models over video so um you have seen maybe a models that can generate images like dali and people are looking into models generating videos they're like various algorithmic questions even how to do it and it's unclear if there is enough compute for this purpose but i i suspect that the models that which would have a level of understanding of video same as gpt has the level of understanding of text could be used to train robots to solve tasks they would have a lot of common sense if one day i'm pretty sure one day there will be a robotics company by robotics company i mean the primary source of income is is from robots that is worth over 1 trillion dollars what do you think that company will do i think self-driving cars no it's interesting because my mind went to personal robotics robots in the home it seems like there's much more market opportunity there i think it's very difficult to achieve i mean this this this might speak to something important which is i understand self-driving much better than understand robotics in the home so i understand how difficult it is to actually solve self-driving to uh to a level not just the actual computer vision and the control problem and just the basic problem self-driving but creating a product that would undeniably be um that will cost less money like it will save you a lot of money like orders the magnitude less money that could replace uber drivers for example so car sharing that's autonomous that creates a similar or better experience in terms of how quickly you get from a to b or just whatever the the pleasantness of the experience the efficiency of the experience the value of the experience and at the same time the car itself costs cheaper i think that's very difficult to achieve i think there's a lot more um low hanging fruit in the home that that could be i also want to give you perspective on like how challenging it would be at home or like it maybe kind of depends on the exact problem that you'd be solving okay if we are speaking about these robotic arms and hence these things they cost tens of thousands of dollars or maybe 100k and you know maybe obviously maybe there would be economy of scale these things would be cheaper but actually for any household to buy the price would have to go down to maybe thousand bucks yeah i personally think that uh so self-driving car it provides a clear service i don't think robots in the home they'll be a trillion dollar company will just be all about service meaning it will not necessarily be about like a robotic arm that helps you i don't know open a bottle or wash the dishes or any of that kind of stuff it has to be able to take care of that whole the therapist thing you mentioned i i think that's um of course there's a line between what is a robot and what is not like doesn't really need a body but you know some uh ai system with some embodiment i think so the tricky part when you think actually what's the difficult part is um when the robot has like when there is a diversity of the environment with which the robot has to interact that becomes hard so you know on one spectrum you have industrial robots as they are doing over and over the same thing it is possible to some extent to prescribe the movements and with very small amount of intelligence the the movement can be repeated millions of times um the it there are also you know various pieces of industrial robots where it becomes harder and harder like for instance in case of tesla it might be a matter of putting a a rack inside of a car and you know because the rack kind of moves around it's it's not that easy it's not exactly the same every time it ends up being the case that you need actually humans to do it and while you know welding cars together it's a very repetitive process and then in case of self-driving itself the difficulty has to do with the diversity of the environment but still the car itself and the problem that you are solving is you try to avoid even interacting with things you are not touching anything around because touching itself is hard and then if you would have in the home uh robot that you know has to touch things and like if these things they change the shape if there is a huge variety of things to be touched then that's difficult if you are speaking about the robot which there is you know head that is smiling in some way with cameras that it doesn't you know touch things that's relatively simple okay so to both agree and to push back so you're referring to touch like soft robotics like the actual touch but i would argue that you could formulate just basic interaction between um like non-contact interaction is also a kind of touch and that might be very difficult to solve that's the basic this not disagreement but that's the basic open question to me with self-driving cars and disagreement with elon which is how much interaction is required to solve self-driving cars how much touch is required you said that in your intuition touch is not required and my intuition to create a product that's compelling to use you're going to have to uh interact with pedestrians not just avoid pedestrians but interact with them when we drive around in major cities we're constantly threatening everybody's life with our movements and that's how they respect us there's a game theoretically going on with pedestrians and i am afraid you can't just formulate autonomous driving as a collision avoidance problem so i i think it goes beyond like a collision avoidance is the first order approximation but then at least in case of tesla they are gathering data from people driving their cars and i believe that's an example of supervised learning data that they can train their models uh on and they are doing it which you know can give the model this like another level of of a behavior that is needed to actually interact with the real world yeah it's interesting how much data is required to achieve that um what do you think of the whole tesla autopilot approach the computer vision based approach with multiple cameras and there's a data engine it's a multi-task multi-headed neural network and it's this fascinating process of uh similar to what you're talking about with the the robotics approach uh which is you know you deploy neural network and then there's humans that use it and then it runs into trouble in a bunch of places and that stuff is sent back so like the deployment discovers a bunch of edge cases and those edge cases are sent back for supervised annotation thereby improving the neural network and that's deployed again it goes over and over until the the network becomes really good at the task of driving becomes safer and safer what do you think of that kind of approach to robotics i believe that's the way to go so in some sense even when i was speaking about you know collecting trajectories from humans that's like a first step and then you deploy the system and then you have humans revising the all the issues and in some sense like this approach converges to system that doesn't make mistakes because for the cases where there are mistakes you got their data how to fix them and the system will keep on improving so there's a very to me difficult question of how hard that you know how long that converging takes how hard it is uh the other aspect of autonomous vehicles this probably applies to certain robotics applications is society right they put as as the quality of the system converges so one there's a human factors perspective of psychology of humans being able to supervise those uh even with teleoperation those robots and the other society willing to accept robots currently society is much harsher on self-driving cars than it is on human driven cars in terms of the expectation of safety so the bar is set much higher than for humans and we're so if there's a death in an autonomous vehicle that's seen as much more much more dramatic than a death in a human driven vehicle part of the success of deployment of robots is figuring out how to make robots part of society both on the just the human side on the media journalist side and also on the policy government side and that seems to be uh maybe you can put that into the objective function to optimize but that is that is definitely um a tricky one and i wonder if that is actually the trickiest part for self-driving cars or any system that's safety critical it's not the algorithm it's the society accepting it yeah i i would say i believe that the part of the process of deployment is actually showing people that the given things can be trusted yeah and you know trust is also like a glass that is actually really easy to crack it yeah and damage it and i think that's actually very common with uh with innovation that there is some resistance toward it yeah and it's just the natural progression so in some sense people will have to keep on proving that indeed these systems are worth being used and i would say i also found out that often the best way to convince people is by letting them experience it yeah absolutely that's the case for tesla autopilot for example that's the case with uh yeah with basically robots in general it's it's kind of funny to hear people talk about robots like there's a lot of fear even like legged robots but when they actually interact with them there's joy i love interacting with them and the same with the car with the robot if it starts being useful i think people immediately understand and if the product is designed well they fall in love you're right it's actually even similar when i'm thinking about co-pilot the github co-pilot there was a spectrum of responses that people had and uh ultimately uh the important piece was to let people try it out and then many people just loved it especially like programmers yeah programmers but like some of them you know they came with a fear yeah but then you try it out and you think actually that's cool okay and you know you can try to resist the same way as you know you could resist moving from punch cards to let's say c plus or so and it's a little bit futile so we talked about generation program generation of language even self-supervised learning in the visual space for robotics and then reinforcement learning what do you and like this whole beautiful spectrum of ai do you think is a good benchmark a good test to strive for to achieve intelligence that's a strong test of intelligence you know it started with alan turing and the touring test maybe you think natural language conversation is a good test so you know it would be nice if for instance machine would be able to solve riemann hypothesis in math that would be i think that would be very impressive so theorem proving is that to you proving theorems is a good oh oh like one thing that the machine did you would say damn exactly okay that would be quite quite impressive i mean the the tricky part about the benchmarks is um you know as we are getting closer with them we have to invent new benchmarks there is actually no ultimate benchmark out there yeah see my thought with the riemann hypothesis would be the moment the machine proves it would say okay well then the problem was easy that's what happens and i mean in some sense um that's actually what happens over the years in ai that like uh we get used to things very quickly you know something i talked to rodney brooks i don't know if you know that is he called alpha zero homework problem because he was saying like there's nothing special about it it's not a big leap and i i didn't well he's coming from one of the aspects that we referred to as he was part of uh the founding of irobot which deployed now tens of millions of robot in the home so if you see robots that are actually in the homes of people as the legitimate instantiation of artificial intelligence then yes maybe an ai that plays a silly game like going chess is not a real accomplishment but to me it's it's a fundamental leap but i think we as humans then say okay well then that uh that game of chess or go wasn't that difficult compared to the thing that's currently unsolved so my intuition is that from perspective of the evolution of you know these ai systems we'll at first see the tremendous progress in digital space and the you know the main thing about digital space is also that you can everything is that there is a lot of recorded data plus you can very rapidly deploy things to billions of people while in case of uh physical space the deployment part takes multiple years you have to manufacture things and you know delivering it to actual people it's very hard so i'm expecting that the first and the prices in digital space of goods they would go you know down to the let's say marginal costs are to zero and also the question is how much of our life will be in digital because it seems like we're heading towards more and more of our lives being in the digital space so like innovation in the physical space might become less and less significant like why do you need to drive anywhere if most of your life is spent in virtual reality i still would like you know to at least at the moment my impression is that i would like to have a physical contact with other people and that's very important to me and we don't have a way to replicate it in the computer it might be the case that over the time it will change like in 10 years from now why not have like an arbitrary infinite number of people you can interact with some of them are real some are not with uh arbitrary characteristics that you can define based on your own preferences i think that's maybe where we are heading and maybe i'm resisting the future yeah i'm telling you i if i got to choose if i could live in elder scrolls skyrim versus the real world i'm not so sure i would stay with the real world yeah i mean the question is so will vr be sufficient to get us there or do do you need to you know plug electrodes in the brain and it would be nice if these electrodes wouldn't be invasive yeah or at least like provably non-destructive but in in the digital space do you do you think we'll be able to solve the touring test the spirit of the touring test which is do you think we'll be able to achieve compelling natural language conversation between people like have friends that are ai systems on the internet i thought i think it's doable do you think the current approach of gbt will take us there so there is you know the the part of at first learning all the content out there and i i think that steel system should keep on learning as it speaks with you yeah and i think that should work the question is how exactly to do it and you know obviously we have people at open air asking these questions and kind of at first pre-training on all existing content is like a backbone and it's a decent backbone do you think ai needs a body connecting to our robotics question to uh truly connect with humans or can can most of the connection be in the digital space so let's see we know that there are people who met each other online and they felt in love yeah so it seems that it's conceivable to establish connection which is purely through internet and of course it might be more compelling than more modalities you add so it would be like you're proposing like a tinder but for ai are you like swipe right and left and half the systems are ai and the other is uh humans and you don't know which is which that would be ours that would be our formulation of touring test the the moment ai is able to achieve more swipe right or left whatever the the moment is able to be more attractive than other humans it passes the torrent test then you would pass the turing test in attractiveness that's right well no like attractiveness just declare conversation not just visual right it's also attractiveness with wit and humor and uh whatever whatever makes conversations pleasant for humans okay all right um so so you're saying uh it's possible to achieve in the digital space in some sense i would almost ask that question why wouldn't that be possible right well i have this argument with my dad all the time he thinks that touch and smell are really important so they can be very important and i'm saying the initial systems they won't have it still i wouldn't like their people being born without these senses and you know i believe that they can still fall in love and have meaningful life yeah i wonder if it's uh possible to go close to all the way by just training on transcripts of conversations like i wonder how far that takes us so i i think that actually still you want images like i would like so i don't have kids but like i could imagine the having ai tutor it has to see you know kids drawing some pictures on their paper and and also facial expressions and all that kind of stuff we use uh dogs and humans use their eyes and uh to communicate with each other i think this that's that's a really powerful mechanism of communication body language too that uh words are much uh lower bandwidth and for body language we still you know we kind of have a system that displays an image of its or facial expression on the computer it doesn't have to move you know mechanical pieces or so so i think that uh you know there is like kind of a progression you can imagine that text might be the simplest to tackle but this is not a complete human experience at all you expand it to let's say images both for input and output and what you describe is actually the final i guess frontier what makes us human the fact that we can touch each other or smell or so and it's the hardest from perspective of data and deployment and i okay i believe that these things might happen gradually are you excited by that possibility this particular application of human to ai friendship and interaction so let's see like would you uh do you look forward to a world you you said you're living with a few folks and you're very close friends with them do you look forward to a day where one or two of those friends are ai systems so if the system would be truly wishing me well rather than being in the situation that it optimizes for my time to interact with the system the line between those is it's a gray it's a gray area i i think that's the distinction between love and possession and these things they might be often correlated for humans but it's it like like a you you might find that there like some friends with whom you haven't spoken for months yeah and then you know you pick up the phone it's as the time hasn't passed they are not holding to you and i will i wouldn't like to have ai system that you know it's it's trying to convince me to spend time with it i would like the system to optimize for what i care about and help me in achieving my own goals but there's some i mean i don't know there's some manipulation there's some possessiveness there's some insecurities this fragility all those things are necessary to form a close friendship over time to go through some dark shit together some bliss and happiness together i feel like there's a lot of greedy self-centered behavior within that process my intuition but i might be wrong is that human computer interaction doesn't have to go through uh computer being greedy possessive and so on it is possible to train systems maybe that they actually you know they are i guess prompted or fine-tuned or so to truly optimize for what you care about and you could imagine that you know that the way how the process would look like is at some point we as a human as we look at the transcript of the conversation or like an entire interaction and we say actually here there was more loving way to go about it and we supervise system toward being more loving or maybe we train the system such that it has a reward function toward being more loving yeah or maybe the possibility of the system being an asshole and manipulative and possessive every once in a while is a feature not a bug because some of the happiness that we experience when two souls meet each other when two humans meet each other is a kind of break from the assholes in the world and so you need assholes and ai as well because like it'll be like a breath of fresh air to discover an ai that the three previous ais you had are too friendly or no no or or cruel or whatever it's like some kind of mix and then this one is just right but you need to experience the full spectrum like i think you need to be able to engineer assholes so let's see because there's some level to us of being appreciate to appreciate the human experience we need the dark and the light so that kind of reminds me um i met a while ago at the meditation retreat uh one woman and um you know beautiful beautiful woman and she had a she had a crutch okay she had the trouble uh walking on one deck i asked her what has happened and she said that five years ago she was in maui hawaii and she was eating a salad and some snail fell into the salad and apparently there are neurotoxic snails over there and she got into coma for a year okay oh wow and apparently there is you know high chance of even just dying but she was in the coma at some point she regained partially consciousness she was able to hear people in the room people behave as she wouldn't be there you know at some point she started being able to speak but she was mumbling like a barely able to to express herself and at some point she got into wheelchair then at some point she actually noticed that she can move her uh a toe and then she knew that she will be able to walk and then you know that's where she was five years after and she said that since then she appreciates the fact that she can move her toe and i was thinking do i need to go through such experience to appreciate that i have i can move my toe well that's really good story a really deep example yeah and in some sense it might be the case that we don't see light if we haven't went through the darkness but i wouldn't say that we should we shouldn't assume that that's the case which may we maybe will do engineer shortcuts yeah ilia had this you know belief that maybe one has to go for a week or six months to some challenging camp yeah to just experience you know a lot of difficulties and then comes back and actually everything is bright everything is beautiful i'm with iliana it must be a russian thing where are you from originally i'm i'm polish polish okay i'm tempted to say that explains a lot but uh yeah there's something about the russian the necessity of suffering i believe i believe suffering or rather struggle is necessary i believe that struggle is necessary i mean in some sense you even look at the story of any superhero in that movie it's not that it was like everything like it goes easy easy i like how that's your ground truth it's the story of superheroes okay uh you mentioned that you used to do research at night and go to bed at like 6 a.m or 7 a.m i still do that often um what uh sleep schedules have you tried to make for a productive and happy life like is there um is there some interesting wild sleeping patterns that you engaged that you found that works really well for you i tried at some point decreasing number of hours of sleep like gradually like a half an hour every few days less you know i was hoping to just save time that clearly didn't work for me like at some point there's like a phase shift and i felt tired all the time uh you know there was a time that i used to work during the nights the nice thing about the nights is that no one disturbs you and even i remember when i was meeting for the first time with greg brookman his cto and chairman of openai our meeting was scheduled to 5 pm and i overstepped for the meeting over slept for the meeting yeah 5 p.m yeah now you sound like me that's hilarious okay yeah and uh at the moment in some sense uh my sleeping schedule also has to do with the fact that i'm interacting with people i sleep without an alarm so so yeah the the team thing you mentioned extrovert thing because most humans operate during a certain set of hours you're forced to then operate at the same set of hours but i'm not quite there yet i found a lot of joy just like you said working through the night because it's quiet because the world doesn't disturb you and there's some aspect counter to everything you're saying there's some joyful aspect to sleeping through the mess of the day because uh people are having meetings and sending emails and there's drama meetings i can sleep through all the meetings you know i have meetings every day and they prevent me from having sufficient amount of time for focus work and then i modified my calendar and i said that i'm out of office wednesday thursday and friday every day and i'm having meetings only monday and tuesday and that vastly positively influenced my mood that i have literally like had three days for fully focused work yeah so there's better solutions to this problem than staying awake all night okay you've been part of development of some of the greatest ideas in artificial intelligence what would you say is your process for developing good novel ideas you have to be aware that clearly there are many other brilliant people around so you have to ask yourself a question why the given idea let's say wasn't uh tried by someone else and in some sense it has to do with you know kind of simple it might sound simple but like i'm thinking outside of the box and what do i mean here so for instance for a while people in academia they assumed that you have a fixed data set and then you optimize the algorithms in order to get the best performance and that was so in great assumption that no one thought about training models on anti-internet or like that that maybe some people thought about it but if it felt too too many as unfair and in some sense that's almost like a it's not my idea or so but that's an example of breaking a typical assumption so you want to be in the paradigm that you are breaking a typical assumption in the context of the ai community getting to pick your dataset as cheating correct and in some sense so that was a that was assumption that many people had out there and then if you free yourself from assumptions then they are likely to achieve something that others cannot do and in some sense if you are trying to do exactly the same things as others it's very likely that you're gonna have the same results yeah i but there's also that kind of tension which is uh asking yourself the question why haven't others done this because um i mean i get a lot of good ideas but i think probably most of them suck when they meet reality so so actually i think the other big piece is uh getting into habit of generating ideas training your brain toward generating ideas and not even suspending judgment of the ideas so in some sense i noticed myself that even if i'm in the process of generating ideas if i tell myself oh that was a bad idea then that actually interrupts the process and i cannot generate more ideas because i'm actually focused on the negative part why it won't work yes but i created also environment in the way that it's very easy for me to to store new ideas so for instance next to my bed i have a voice recorder and it happens to me often like i wake up in that during the night and i have some idea in the past i was writing them down on my phone but that means you know turning off this turning on the screen and that wakes me up or like pulling a paper which requires you know turning on the light these days i just start recording it what do you think i don't know if you know who jim keller is i know team color he's a big proponent of thinking hard on a problem right before sleep so that he can sleep through it and solve it in a sleep or like come up with radical stuff in his sleep he was trying to get me to do this so it happened from my experience perspective it happened to me many times during the high school days when i was doing mathematics that i had the solution to my problem as i woke up at the moment regarding thinking hard about the given problem is i'm trying to actually devote substantial amount of time to think about important problems not just before the sleep like i'm organizing amount of the huge chunks of time such that i'm not constantly working on the urgent problems but i actually have time to think about the important one so you do it naturally but his idea is that you kind of prime your brain to make sure that that's the focus you know oftentimes people have other worries in their life that's not fundamentally deep problems like i don't know uh just stupid drama in your life and even at work all that kind of stuff he wants to kind of pick the most important problem that you're thinking about and go to bed on that i think that's why i mean the other thing that comes to my mind is also i feel the most fresh in the morning so during the morning i try to work on the most important things rather than i'm just being pulled by urgent things or checking email or so what do you do with the cause i've been doing the voice recorder thing too but i end up recording so many messages it's hard to organize i have the same problem now i have heard that google pixel is really good in transcribing text and i might get a google pixel just for the sake of transcribing text yeah people listening to this if you have a good voice recorder suggestion that transcribed please let me know i it's some of it is uh this has to do with uh uh open ai codex too like some of it is simply like the friction i need uh apps that remove that friction between voice and the organization of the resulting transcripts and all that kind of stuff um but yes you're right absolutely like during uh for me it's walking sleep too but walking and running especially running get a lot of thoughts during running and there's there's no good mechanism for recording thoughts so one more thing that i do i have a separate phone uh which i which has no apps and maybe it has like a audible or let's say kindle no one has this phone number this kind of my meditation phone yeah and i try to expand the amount of time that that's the phone that i'm having i it has also google maps if i need to go somewhere and i also use this phone to write down ideas ah that's really good idea that's a really good idea often actually what i end up doing is even sending a message from that phone to the other phone so that's actually my way of recording messages or i just put them into notes i love it what advice would you give to a young person high school college about how to be successful you've done a lot of incredible things in the past decade so maybe maybe of some something there might be something there might be something i mean might sound like a simplistic or so but i would say literally just follow your passion double down on it and if you don't know what's your passion just figure out what could be a what could be a passion so this that might be an exploration when i was in elementary school was math and chemistry and i remember for some time i gave up on math because my school teacher she told me that i'm dumb and i i i guess maybe an advice would be just ignore people if they tell you that you're dumb you mentioned something offline about chemistry and explosives um what was that about so let's see so a story goes like that i can i got into chemistry maybe i was like a second grade of my elementary school third grade uh i started going to chemistry classes uh i i really love building stuff and i did all the experiments that they described in the book okay you know how to create oxygen with vinegar and and baking soda so okay so i did all the experiments and at some point i was you know so what's next what can i do and uh explosives they also it's like a you have a clear reward signal you know if the thing worked or not so i remember at first i got i got interested in producing hydrogen that was kind of funny experiment from school you can just burn it and then i moved to uh nitroglycerin so that's also relatively easy to synthesize i started producing essentially dynamite and detonating with it with my friend i remember there was a you know there was at first like maybe two attempts that i went with a friend to detonate what we built and it didn't work out and like a third time he was like ah it won't work like uh let's don't waste time and um now we were i was carrying this uh this you know that tube with dynamite i don't know pound or so dynamite in my backpack or like riding on the bike to the edges of the city [Laughter] yeah and attempt number three this would be to number three attempt number three and uh now we we dig a hole to uh put it inside it actually had the uh you know electrical detonator we we draw a cable behind the tree i even i never had i haven't ever seen like a explosion before so i thought that there will be a lot of sound and but you know we're like laying down and i'm holding the cable and the battery at some point you know it kind of like a three to one and uh i just connected it and it felt like at the ground shake it was like a more like a sound and then the soil started kind of lifting up and started falling on us yeah wow and then uh now the friends said let's let's make sure next time we have helmets but also you know i'm happy that nothing happened to me it could have been the case that i i lost the limb or so yeah but that's childhood of an engineering mind with a strong reward signal of an explosion i love it my there's some aspect of uh chemists the the the chemist i know like my dad with plasma chemistry plasma physics he was very much into explosives too it's a worrying quality of people that work in chemistry that they love i think it is that exactly is the the strong signal that the thing worked there is no doubt there's no doubt there's some magic it's almost like a reminder that physics works that chemistry works it's cool it's almost like a little glimpse at nature that you yourself engineer i that's why i really like artificial intelligence especially robotics is you create a little piece of nature and in some sense even for me with explosives the motivation was creation rather than distraction yes exactly in terms of advice i forgot to ask about just machine learning and deep learning for people who are specifically interested in machine learning how would you recommend they get into the field so um i would say implement everything and also there is plenty of courses so like from scratch um so on different levels of abstraction in some sense but i would say brain or implement something from scratch or implement something from a paper or implement something you know from podcasts that you have heard about i would say that's a powerful way to understand things so it's often the case that you read the description and you think you understand but you truly understand once you build it then you actually know what really meant that in the description is there particular topics that you find people just fall in love with so i i've seen i tend to uh really enjoy reinforcement learning because it's it's much more it's much easier to get to a point where you feel like you created something special like like fun games kind of things that are rewarding it's rewarding yeah uh as opposed to like uh reimplementing from scratch more like supervised learning kind of things it's it's yeah so you know if if someone would optimize for things to be rewarding then it feels that the things that are somewhat generative they have such a property so yes you have for instance yes adversarial networks or you have just even generated language models and you could you can even see um internally we have seen this thing with our releases so we have a we released recently two models there is one model called dali that generates images and there is other model called clip that actually uh you provide various possibilities what could be the answer to what is on the picture and it can tell you which one is the most likely okay and in some sense in case of the first one dali it is very easy for you to understand that actually there is magic going on uh and in the in case of the second one even though it is insanely powerful and you know people from a vision community they as they started probing it inside they actually understood how far it goes it's difficult for person at first to see how well it works and that's the same as you said that in case of supervised learning models you might not kind of see or it's not that easy for you to understand the the strength even though you don't believe in magic to see the magic let's say that magic it's a generative that's really brilliant so anything that's generative because then you are at the core of the creation you get to experience creation without much effort unless you have to do it from scratch but and it feels that you know humans are wired there is some level of reward for creating stuff yeah like of course different people have a different weight on this reward yeah in the big objective function in the big objective of a person of a person uh you wrote that beautiful is what you intensely pay attention to even a cockroach is beautiful if you look very closely can you expand on this what is beauty so what i'm i wrote here actually corresponds to my subjective experience that i had through extended periods of meditation it's it's pretty crazy that at some point the meditation gets you to the place that you have really increased uh focus increase attention and then you look at the very simple objects that were all the time around you can look at the table or on the pen or at that nature and you notice more and more details and it becomes very pleasant to look at it and it once again it kind of reminds me my childhood uh like i just pure joy of being it's also i have seen even the reverse effect that by default regardless of what we possess we very quickly get used to it and you know you can have a very beautiful house and if you don't put sufficient effort you're just gonna get used to it and it doesn't bring any more joy regardless of what you have yeah well i actually i find that material possessions get in the way of that experience of pure joy so i've always i've been very fortunate to just find joy in simple things just just like you're saying just like i don't know objects in my life just stupid objects like this cup like thing you know just objects sounds okay i'm not being eloquent but literally objects in the world they're just full of joy because it's like i can't believe one i can't believe that i'm fortunate enough to be alive to experience these objects and then two i can't believe humans are clever enough to have built these objects the the hierarchy of pleasure that that uh provides is infinite i mean even if you look at the cup of water so you know you see first like a level of like a reflection of light but then you think you know man there's like a trillions upon of trillions of particles bouncing uh against each other there is also uh the tension on the surface that you know if the back back could like a stand on it and move around and you think it also has this like a magical property that as you decrease temperature it actually expands in volume which allows for the you know legs to freeze on the on the surface and then at the bottom to have actually uh not freeze which allows for life like a crazy yeah you look in detail at some object and you think actually you know this table that was just the figment of someone's imagination at some point and then there was like thousands of people involved to actually manufacture it yeah and put it here and by default no one cares [Laughter] and then you can start thinking about evolution how it all started from single cell organisms that led to this table and and okay these thoughts they give me life appreciation yeah and even lack of those just the pure raw signal also gives their life appreciation see the thing is and then that's coupled for me with the sadness that the whole ride ends and perhaps is deeply coupled in that the fact that this experience this moment ends gives it gives it an intensity that i'm not sure i would otherwise have so in that same way i try to meditate on my own death often do you think about your mortality are you afraid of death so fear of death is like one of the most fundamental fears that each of us has we might be not even aware of it it requires to look inside to even recognize that it's out there and there is still let's say this property of uh nature that if things would last forever then they would be also boring to us the fact that the things change in some way gives any meaning to them i also you know found out that it seems to be very healing to people to have this short experiences uh like i guess psychedelic experiences in which they experience death of self in which they let go of this fear and then maybe can even increase the appreciation of the moment and it seems that many people they uh they they can easily comprehend fine the fact that their money is finite while they don't see that time is finite i have this like a discussion with ilya from time to time he's saying you know man like uh the lack will pass very fast at some point i will be 40 50 60 70 and then it's over this is true which also makes me believe that you know that every single moment it is so unique that should be appreciated and this also makes me think that i should be acting on my life because otherwise it will pass i also like this framework of thinking from jeff bezos on regret minimization that like i would like if i will be at that death bed to look back on my life and and not regret that i haven't done something it's usually you might regret that you haven't tried i'm fine with failing i haven't tried uh what's the nature eternal occurrence tried to live a life that if you had to live it infinitely many times that would be the you'll be okay with that kind of life so try to live it optimally i can say that it's almost like i'm unbelievable to me where i am in my life i'm extremely grateful for actually people whom i met i would say i think that i'm decently smart and so on uh but i think that actually to great extent where i am has to do with that people who i met would you be okay if after this conversation you died so if i'm dead then it kind of i don't have a choice anymore so in some sense there's like plenty of things that i would like to try out in my life [Music] i feel that you know i'm gradually going one by one and i'm just doing them i think that the list will be always infinite yeah so might as well go today yeah i mean to be clear i'm not looking forward to die i would say if there is no choice i would accept it but like uh in some sense i'm if there would be a choice if there would be possibility to live i would fight for a living i find um it's more honest than real to think about you know dying today at the end of the day that seems to me to at least to my brain more honest slap in the face as opposed to i still have 10 years like today then then i'm much more about appreciating the cup and the table and so on and less about like silly worldly accomplishments and all those kinds of things we we have in the company a person who say at some point found out that they have cancer and that also gives you know huge perspective with respect to what matters now yeah and you know often people in situations like that they conclude that actually what matters is human connection and love and uh that's people conclude also if you have kids because kids is family you uh i think tweeted we don't assign the minus infinity reward to our death such a reward would prevent us from taking any risk we wouldn't be able to cross the road in fear of being hit by a car so in the objective function you mentioned fear of death might be fundamental to the human condition so as i said let's assume that they're like a reward functions in our brain and and the interesting thing is even realization how different reward functions can play with your behavior as a matter of fact i wouldn't say that you should assign infinite negative reward to anything because that messes up the math the math doesn't work out it doesn't work out and as you said even you know uh government or some insurance companies you said they assign 99 million dollars to human life yeah and i'm just saying it with respect to that might be a harsh statement to ourselves but in some sense that there is a finite value of our own life i'm trying to put it from perspective of being less of being more egoless and realizing fragility of my own life and in some sense the fear of death might prevent you from acting because anything can cause death yeah and i'm sure actually if you were to put death in the objective function there's probably so many aspects to death and fear of death and realization of death and mortality there's just whole components of finiteness of not just your life but every experience and so on you're gonna have to formalize mathematically and also you know that might lead to um you spending a lot of compute cycles on this like a and deliberating this terrible future instead of experiencing now and that in some sense is also kind of unpleasant simulation to run in your head yeah do you think there's an objective function that describes the entirety of uh human life so you know usually the way you ask that is what is the meaning of life is there um a universal objective functions that captures the why of life so yeah i mean i suspected that they will ask this question but it's also a question that i asked myself many many times see i can tell you a framework that i have these days to think about these questions so i think that fundamentally meaning of life has to do with some of our reward functions that we have in brain and they might have to do with let's say for instance curiosity or human connection which might mean understanding others it's also possible for a person to slightly modify their reward function usually they mostly stay fixed but it's possible to modify reward function and you can pretty much choose so in some sense reward functions optimizing reward functions they will give you life satisfaction is there some randomness in the function i think when you are born there is some randomness like you can see that some people for instance they they care more about building stuff some people care more about caring for others some people that there are all sorts of uh default reward functions and then in some sense you can ask yourself what's this like what is the satisfying way for you to go after this reward function and you just go after this reward function and you know some people also ask are these reward functions real i almost think about it as let's say if you would have to discover mathematics in mathematics you are likely to run into various objects like a complex numbers or differentiation some other objects and these are very natural objects that arise and similarly the reward functions that we are having in our brain they are somewhat very natural that you know there is a reward function for for understanding like a comprehension yeah uh curiosity and so on so in some sense they are in the same way natural as their natural objects in mathematics interesting so you know there's the uh the old sort of debate is mathematics invented or discovered you're saying reward functions are discovered so nature so nature's provided some you can still let's say expanded throughout the life some of the reward functions they might be futile like for instance there might be a reward function maximize amount of wealth yeah and this is more like a a learning reward function and but we know also that some reward functions if you optimize them you won't be quite satisfied well i don't know which part of your reward function resulted in you coming today but i am deeply appreciative that you did spend your valuable time with me watching is really fun talking to you you're you're brilliant you're a good human being and it's an honor to meet you and an honor to talk to you thanks for talking today brother thank you alex a lot i appreciated your questions here i had a lot of time being here thanks for listening to this conversation with welch and ramba to support this podcast please check out our sponsors in the description and now let me leave you some words from arthur c clarke who is the author of 2001 a space odyssey it may be that our role on this planet is not to worship god but to create him thank you for listening and hope to see you next time you