#373 – Manolis Kellis: Evolution of Human Civilization and Superintelligent AI

29:50And the fact that it's encoded in an orthogonal way from the knowledge, I think, is also beautiful. The fact that somehow, through this extreme overperimentalization of AI models, it was able to somehow figure out that context, knowledge and form are separable, and that you can sort of describe scientific knowledge in a haiku in the form of, I don't know, Shakespeare or something. That tells you something about the decoupling and the decoupling of these types of aspects of human psyche. And that's part of the science of this whole thing. So these large language models are, you know, days old in terms of this kind of leap that they've taken.

30:34And it would be interesting to do this kind of analysis on them of context, of the separation of context, form and knowledge. Where exactly does that happen? There's already initial investigations, but it's very hard to figure out where their particular parameters that are responsible for a particular piece of knowledge or particular context or particular style speaking. So with convolutional neural networks, interpretability had many good advances because we can kind of understand them. There's a structure to them. There's a locality to them and we can kind of understand the different layers have different sort of ranges that they're looking at.

31:14So we can look at activation features and basically see where, you know, where does that correspond to. With large language models, it's perhaps a little more complicated, but I think it's still achievable in the sense that we could kind of ask, well, what kind of prompts does this generate if I sort of drop out this part of the network than what happens and sort of start getting at a language to even describe these types of aspects of human behavioral psychology, if you wish, from the spoken part in the language part. And the advantage of that is that it might actually teach us something about humans as well.

31:51Like, you know, we might not have words to describe these types of aspects right now, but when somebody speaks in a particular way, it might remind us of a friend that we know from here and there and there. And if we had better language for describing that, these concepts might become more apparent in our own human psyche. And then we might be able to encode them better in machines themselves. Well, probably you and I would have certain interest with the base model, with OpenEck or the base model, which is before the alignment of the reinforcement learning with human feedback and before the AI safety -based kind of censorship of the model.

32:32It would be fascinating to explore, to investigate the ways that the model can generate hate speech, the kind of hate the humans are capable of. It would be fascinating. Or the kind of, of course, like sexual language, or the kind of romantic language, or the all kinds of ideologies. Can I get it to be a communist? Can I get it to be a fascist? Can I get it to be a capitalist? Can I get it to be all these kinds of things and see which parts get activated and not? Because it will be fascinating to sort of explore at the individual mind level and at a societal level, where do these ideas take hold?

33:12What is the fundamental core of those ideas? Maybe the communism, fascism, capitalism, democracy are all actually connected by the fact that the human mind is drawn to ideology, to a centralizing idea. Maybe we need a new network to remind us of that. I like the concept that the human mind is somehow tied to ideology. I think that goes back to the promptability of JGPT, the fact that you can kind of say, well, thinking this particular way now, and the fact that humans have infected words for encapsulating these types of behaviors. And it's hard to know how much of that is innate and how much of that was like passed on from language to language.

33:55But basically if you look at the evolution of language, you can kind of see how young are these words in the history of language evolution that describe these types of behaviors like, you know, kindness and anger and jealousy et cetera. If these words are very similar from language to language, it might suggest that but they're very ancient. If they're very different, it might suggest that this concept may have emerged independently in each different language and so forth. So looking at the phylogeny, the history, the evolutionary traces of language at the same time as people moving around, that we can now trace, thanks to genetics, is a fascinating way of understanding the human psyche and also understanding sort of how these types of behaviors emerge.

34:49And to go back to your idea about sort of exploring the system unfiltered, I mean, in a way, this is psychiatric hospitals are filled with those people. So basically people whose mind is uncontrollable, who have kind of gone adrift in specific locations of their psyche. And I do find this fascinating. Basically, watching movies that are trying to capture the essence of troubled minds, I think is teaching us so much about our everyday selves because many of us are able to sort of control our minds and are able to somehow hide these emotions. But every time I see somebody who struggled, I see versions of myself, maybe not as extreme, but I can empathize with these behaviors.

35:45And I see bipolar, I see schizophrenia, I see depression, I see autism, I see so many different aspects that we have names for and crystallize in specific individuals. And I think all of us have that. All of us have this multidimensional brain and genetic variations that push us in these directions, environmental exposures and traumas that push us in these directions, environmental behaviors that are reinforced by the kind of friends that we chose or friends that we were stuck with because of the environments that we grew up in. So, in a way, a lot of these types of behaviors are within the vector span of every human.

36:32It's just that the magnitude of those vectors is generally smaller for most people because they haven't inherited that particular set of genetic variants or because they haven't been exposed to those environments basically. Or something about the mechanism of reinforcement learning with human feedback didn't quite work for them. So it's fascinating to think about that's what we do. We have this capacity to have all these psychiatric or behaviors there's associated with psychiatric disorders, but we through the alignment process as we go off of your parents, we kind of, we know to suppress them.

37:09We know how to control. Every human that grows up in this world spends several decades being shaped into place. And without that, you know, maybe we would have the unfiltered chat GPT -4. Every baby is basically a raging narcissist. Not all of them. Not all them. Believe it or not. It's remarkable. Like I remember watching my kids grow up and again, yes, part of their personality has stays the same, but also in different phases to their life, they've gone through these dramatically different types of behaviors. And my daughter basically saying, basically one kid saying, oh, I want the bigger piece, the other one saying, Oh, everything must be exactly equal.

37:54And the third one's saying, I'm OK. You know, I might have to have the smaller part. Don't worry about me. Even in the early days, in the early days of development. Yeah. It's just extraordinary to sort of see these dramatically different. I mean, my wife and I are very different from each other. But we also have six million variants, six million low -size each, if you wish, if you just look at common variants, we also have a bunch of rare variants that are inherited in more Mendelian fashion. And now you have an infinite number of possibilities for each of the kids. So basically it's due to the 6 million just from the common variance and then if you like layer in the rare variance.

38:33So let me talk a little bit about common variance and rare variance. So if you look at just common variance, they're generally weak effect because selection selects against strong effect variance. So if something like has a big risk for schizophrenia, it won't rise to high frequency. So the ones that are common are by definition, by selection, only the ones that had relatively weak effect. And if all of the variants associated with personality, with cognition and all aspects of human behavior, where weak effect variance, then kids would basically be just averages of their parents. If it was like thousands of low -sci, just by large numbers, the average of two large numbers would be very robustly close to that middle.

39:17But what we see is that kids are dramatically different from each other. So that basically means that in the context of that common variation, you basically have rare variants that are inherited in a more Mendelian fashion, that basically then sort of govern likely many different aspects of human behavior, human biology, and human psychology. And that's, again, if you look at sort of a person with schizophrenia, their identical twin has only 50 % chance of actually being diagnosed with schizophrenia. So that basically means there's probably developmental exposures and environmental exposures, trauma, all kinds of other aspects that can shape that.

39:59And if you look at siblings, for the common variants, it kind of drops off exponentially as you would expect with, you know, sharing 50 % of your genome, 25 % of your genome, you know, 12 .5 % of your genome, etc, with more and more distant and cousins. But the fact that siblings can differ so much in their personality is that we observe every day, it can't all be nurture. Basically, again, as parents, we spend enormous amount of energy trying to fix, quote unquote, the nurture part, trying to get them to share, get them to be kind, get them to be open, get them to trust each other, like overcome the prisoners dilemma of, you know, if everyone finds themselves we're all going to live in a horrible place, but if we're a little more altruistic then we're all going to be in a better place.

40:47And I think it's not like we treat our kids differently, but they're just born differently. So in a way, as a geneticist, I have to admit that there's only so much I can do with nurture. That nature definitely plays a big component. The selection of variants we have, the common variants and the What can we say about the landscape of possibility they create? If you can just linger on that. The selection of rare variants is divine how. How do we get the ones that we get? Is it just laden in that giant evolutionary baggage? So I'm going to talk about regression. Why do we call it regression? And the concept of regression to the mean, the fact that when fighter pilots in a dogfight did amazingly well, they would give them rewards.

41:45And then the next time they're in dogfight, they would do worse. So then, you know, the Navy basically realized that wow, at least interpreted that as wow, we're ruining them by praising them and then they're going to perform more. The statistical interpretation of that is regression of the mean. The fact that you're an extraordinary pilot, you've been trained in an extraordinary fashion. That pushes your mean further and further to extraordinary achievement. And then in some dog fights, you'll just do extraordinarily well. The probability that the next one will be just is good is almost nil because this is the peak of your performance and just by statistical odds the next one would be another sample from the same underlying distribution which is going to be a little closer to the mean.

42:36So regression analysis takes its name from this type of realization in the statistical world. Now, if you now take humans, you basically have people who have achieved extraordinary achievements. Einstein, for example, you know, you would call him, for example, the epitome of human intellect. Does that mean that all of his children and grandchildren will be extraordinary geniuses? It probably means that they're sampled from the same underlying distribution, But he was probably a rare combination of extremes in addition to these common variants. So you can basically interpret your kid's variation, for example, as well, of course, they're going to be some kind of sampled from the average of the parents with some kind of deviation according to the specific combination of rare variants that they have inherited.

43:30So, you know, given all that, the possibilities are endless as to sort of where you should be, but you should always interpret that with, well, it's probably an alignment of nature and nurture. And the nature has both the common variants that are acting kind of like the law of large numbers and the rare variants that are acting more in a Mendelian fashion. And then you layer in the nurture, which again, in every day action we make, we shape our future environment, but the genetics we inherit are shaping the future environment of not only us, but also our children. So there's these weird nature, nurture, interplay, and self -reinforcement where you're kind of shaping your own environment, but you're also shaping the environment of your kids.

44:17And your kids are going to be born in the context of your environment that you've shaped, but also with a bag of genetic variants that they have inherited. And there's just so much complexity associated with that. When we start blaming something on nature, it might just be nurture. It might just be that, well, yes, they inherited the genes from the parents, but they also were shaped by the same environment. So it's very, very hard to untangle the two. And you should always realize that nature can influence nurture, nurture can influence nature, or it'll be correlated with and predictive of, and so on and so forth.

44:52So I love thinking about that distribution that you mentioned and here's where I can be my usual ridiculous self and I sometimes think about that army of sperm cells Well, however many hundreds of thousands there are and I kind of think of all the possibilities there Because there's a lot of variation and one gets to win Is that not a random one? It's a totally ridiculous way to think about. Oh, not at all. So I would say, evolutionarily, we are a very slow evolving species. Basically, the generations of humans are a terrible way to do selection. What you need is processes that allow you to do selection in a smaller, tighter loop.

45:39And part of what, if you look at our immune system, for example, it evolves at a much faster pace than humans evolve. Because there is action evolutionary process that happens within our immune cells. As they're dividing, there's basically VDJ recommendation that basically creates this extraordinary wealth of antibodies and antigens against the environment. And basically all these antibodies are now recognizing all these antigens from the environment. and they send signals back that cause these cells that recognize the non -self to multiply. So that basically means that even though viruses evolve at millions of times faster than we are, we can still have a component of ourselves which is environmental -facing, which is sort of evolving at not the same scale, but very rapid pace.

46:36sperm expresses perhaps the most proteins of any cell in the body. And part of the thought is that this might just be a way to check that the sperm is intact. In other words, if you wait it until that human has a liver and starts eating solid food and sort of filtrates away, or kidneys or stomach, etc. If you waited until these mutations manifest late, late in life, then you would end up not failing fast and you would end up with a lot of failed pregnancies and a lot of later onset psychiatric illnesses, etc. If instead you basically express all of these genes at the sperm level and if they form that basically caused the sperm to cripple, then you have at least on the male side the ability to exclude some of those mutations.

47:31And on the female side as the egg develops there's probably a similar process where you could sort of weed out eggs that are just not you know carrying beneficial mutations or at least that are carrying highly detrimental mutations. So you You can basically think of the evolutionary process in a nested loop, basically, where there's an inner loop where you get many, many more iterations to run, and then there's an outer loop that moves at a much slower pace. Going back to the next step of evolution of possibly designing systems that we can use to complement our own biology or to eradicate disease and ename it, or mitigate some of the psychiatric illnesses, neurodegenerative disorders, etc.

48:21You can basically, you know, metabolic, immune, cancer, you name it, simply engineering these mutations from rational design might be very inefficient. If instead you have an evolutionary loop where you're kind of growing neurons on a dish and you're exploring evolutionary space and you're sort of shaping that one protein to be better adept at sort of, I don't know, recognizing light or communicating with other neurons, et cetera, you can basically have a smaller evolutionary loop that you can run thousands of times faster than the speed it would take to evolve humans for another million years.

48:55So I think it's important to think about sort of this evolveability as a set of nested structures that allow you to sort of test many more combinations, but in a more fixed setting. Yeah, that's fascinating. The mechanism there is for sperm to express proteins that create a testing ground early on so that the failed designs don't make it. Yeah, even in design of engineering systems, the fail fast is one of the principles you learn. Like basically you assert something. Why do you assert that? Because if that's something ain't right, you better crash now, then sort of let it crash at an unexpected time.

49:35And in a way, you can think of it as like 20 ,000 assert functions, assert protein can fold, assert protein can fold. And if any of them fail, that's Birmingham. gone. Well, I just like the fact that I'm the winning sperm. I'm the result of the winner. Winning hashtag winning. My wife always plays me this French song that actually sings about that. It's like, you know, remember in life, we were all the first one time. At least one time you were the first. I should mention it as a brief tangent back to the place where we came from. Yeah. Which is the base model that I mentioned for open AI, which is before the reinforcement learning with human feedback and you kind of give this metaphor of it being kind of like a psychiatric hospital like that because it's basically all of these different angles at once like you basically have the more extreme versions of human psyche.

50:25So the interesting thing is what I've talked with folks in OpenAI quite a lot and they say it's extremely difficult to work with that model. Yeah, kind of like it's extremely difficult to work with some humans. The parallels there are very interesting because once you run the alignment processes, it's much easier to interact with it. But it makes you wonder what the capacity, what the underlying capability of the human psyche is, as in the same way that what is the underlying capability of a large language model? And remember earlier when I was basically saying that part of the reason why it's so prompt, malleable is because of that alignment problem, that alignment work.

51:04It's kind of nice that the engineers at OpenAI have the same interpretation that, in fact, it is that. And this whole concept of easier to work with, I wish that we could work with more diverse humans. And that's one of the possibilities that I see with the advent of these large language models. The fact that it gives us the chance to both dial down friends of ours that we can't interpret or that are just too edgy to sort of really truly interact with, where you could have a real -time translator. The same way that you can translate English to Japanese or Chinese or Korean by like real -time adaptation, you could basically suddenly have a conversation with your favorite extremist on either side of the spectrum and just dial them down a little bit.

52:06Of course not you and I, but you could have friends who's a complete asshole, but it's a different base level, so you could actually tune it down to like, okay, they're not actually being an asshole there. They're actually expressing love right now. Yeah. They have their way of doing that. and they probably live in New York before just to pick around them location. So, so, yeah, so you can basically layer out context. You can basically say, ooh, let me change New York to Texas and let me change, you know, extreme left, extreme right or somewhere in the middle or something. And I also like the concept of being able to listen to the information without being dissuaded by the emotions.

52:55In other words, everything human say has an intonation, has some kind of background that they're coming from, reflects the way that they're thinking of you, reflects the impression that they have of you, and all of these things are intertwined, but being able to disconnect them, being able to sort of, I mean, self improvement is one of the things that I'm constantly, working on and being able to receive criticism from people who really hate you is difficult because it's layered in with that hatred. But deep down there's something that they say that actually makes sense. Or people who love you might layer it in a way that doesn't come through.

53:40But if you're able to sort of disconnect that emotional component from the sort of self -improvement and And basically when somebody says, whoa, that was a bunch of bullshit, did you ever do the control dissonally than that? You could just say, oh, thanks for the very interesting presentation. You know, I'm wondering, what about that control? Then suddenly you're like, oh yeah, of course, I'm gonna run that control, that's a great idea. Instead of, that was a bunch of BS, you're like, ah, you're sort of hitting on the brakes and you're trying to push back against of that. So any kind of criticism that comes after that is very difficult to interpret in a positive way because it helps reinforce the negative assessment of your work.

54:20When in fact, if we disconnected the technical component from the negative assessment, then you're embracing the technical component you're going to fix it. Whereas if it's coupled with, and if that thing is real and I'm right about your mistake, then it's a bunch of BS, then suddenly you're going to try to prove that that mistake does not exist. Yes, fascinating to like carry the information. This is what you're essentially able to do here is you carry the information in the rich complexity that information contains. So it's not actually dumbing it down in some ways. It's still expressing it, but taking off, but you can die the emotional.

55:02The emotional side. Yeah, which is probably so powerful for the internet or for social networks. Again, when it comes to understanding each other, Like for example, I don't know what it's like to go through life with a different skin color. I don't know how people will perceive me. I don't know how people will respond to me. We don't often have that experience. But in a virtual reality environment or in a sort of AI interactive system, you could basically say, okay, now make me Chinese or make me South African or make me, you know, Nigerian. You can change the accent, you can change layers of that contextual information, and then see how the information is interpreted.

55:46And you can re -hear yourself through a different angle, you can hear others, you can have others react to you from a different package. And then hopefully we can sort of build empathy by learning to disconnect all of these social cues that we get from like how a person is dressed, you know, if they're wearing a hoodie or if they're wearing a shirt or if they're wearing a jacket, you get very different emotional responses that, you know, I wish we could overcome as humans and perhaps large language models and augmented reality and deep fakes can kind of help us overcome all that. In what way do you think these large language models and the thing they give birth to in the AI space will change this human experience, the human condition.

56:40The things we've talked across many podcasts about that makes life so damn interesting and rich. Love, fear, fear of death, all of it. If we could just begin kind of thinking about how does it change for the good and the bad, the human condition. Human society is extremely complicated. We have come from a hunter -gatherer society to an agricultural and farming society where the goal of most professions was to eat and to survive. And with the advent of agriculture, the ability to live together in societies, humans could suddenly be valued for different skills. If you don't know how to hunt, but you're an amazing potterer, then you fit in society very well because you can sort of make your pottery and you can barter it for rabbits that somebody else caught.

57:49And the person who hunts the rabbits doesn't need to make pots because you're making all the pots. And that specialization of humans is what shaped modern society. And with the advent of currencies and governments and you know credit cards and Bitcoin, you basically now have the ability to exchange value for the kind of productivity that you have. So basically, I make things that are desirable to others, I can sell them and buy back food shelter, etc. With AI, the concept of, I am my profession might need to be revised because I defined my profession in the first place, I something that humanity needed that I was uniquely capable of delivering.

58:37But the moment we have AI systems able to deliver these goods, for example, writing a piece of software or making a self -driving car or interpreting the human genome, then that frees up more of human time for other pursuits. These could be pursuits that are still valuable to society. I could basically be 10 times more productive at interpreting genomes and do a lot more. Or I could basically say, oh great, the interpreting genome is part of my job. Now only takes me 5 % of the time instead of 60 % of the time. So now I can do more creative things. I can explore not new career options, but maybe new directions for my research lab.

59:25I can sort of be more productive, contribute more to society. And if you look at this giant pyramid that we have built on top of the subsistence economy, what fraction of US jobs are going to feeding all of the US? Less than 2%. Basically the gaining productivity such that 98 % of the economy is beyond just feeding ourselves. And that basically means that we kind of have built these system of interdependencies of needed or useful or valued goods that sort of make the economy run that the vast majority of wealth goes to other what we now called needs but used to be once. So basically I want to fly a drone.

1:00:17I want to buy a bicycle. I want to buy a nice car. I want to have a nice home. I want to et cetera, et cetera, et cetera. So, and then sort of what is my direct contribution to my eating? I mean, I'm doing research on the human genome. I mean, this will help humans. It will help all humanity. But how is that helping the person who's giving me poultry or vegetables? So, in a way, I see AI as perhaps leading to a dramatic rethinking of human society. If you think about sort of the economy being based on intellectual goods that I'm producing, what if AI can produce a lot of these intellectual goods and satisfies that need?

1:00:56Does that now free humans for more artistic expression, for more emotional maturing, for basically having a better work life balance, being able to show up for your two hours of work a day or two hours of work like three times a week with like immense rest and preparation and exercise and you're sort of clearing your mind and telling you have these two amazingly creative hours. You basically show up at the office as your AI is busy answering your phone call, making all your meetings, you know, revising all your papers, etc. And then you show up for those creative hours and you're like, all right, autopilot, I'm on.

1:01:33And then you can basically do so so much more that you would perhaps otherwise never get to because you're so overwhelmed with these mundane aspects of your job. So I feel that AI can truly transform the human condition from realizing that we don't have jobs anymore. We now have vocations. And there's this beautiful analogy of three people laying bricks. And somebody comes over and asks the first one, what are you doing? He's like, oh, I'm laying bricks. Second one, what are you doing? I'm building a wall. And the third one, what are you doing? I'm building this beautiful cathedral. So in a way the first one has a job, the last one has a vocation.

1:02:16And if you ask me what are you doing, oh I'm editing a paper, then I have a job. What are you doing? I'm understanding human disease circuitry. I have a vocation. So in a way, being able to allow us to enjoy more of our vocation by taking away offloading some of the job part of our daily activities. So we all become the the buildings of cathedral. Correct. Yeah, and we follow intellectual pursuits, artistic pursuits. I wonder what how that really changes at a scale of several billion people. Everybody playing in the space of ideas and the space of creations. So ideas, maybe for some of us, maybe you and I are in the job of ideas, but other people are in the job of experiences, other people in the job of emotions, of dancing, of creative artistic expression, of skydiving, and you name it.

1:03:18So basically these, again, the pewd of human diversity is exactly that. That what rocks my boat might be very different from what rocks other people's boat and what I'm trying to say is that maybe AI will allow humans to truly Like not just look for but find meaning and sort of you don't need to work But you need to keep your brain at ease and the way that your brain will be at ease is by dancing and creating this amazing movements or creating these amazing paintings or creating, I don't know, something that sort of changes that touches at least one person out there that sort of shapes humanity through that process.

1:04:04And instead of working your mundane programming job where you hate your boss and you hate your job and you say you hate that darn program, et cetera, you're like, well, I don't need that. I can, you know, offload that and I can now explore something that will actually be more beneficial to humanity because the mundane parts can be offloaded. I wonder if it localizes our, all the things you mentioned, all the vocations. So you mentioned that you're not might be playing in the space of ideas, but there's two ways to play in the space of ideas, both of which we're currently engaging. So one is the communication of that to other people.

1:04:42It could be a classroom full of students, but it could be podcasts. It could be something that's shown on YouTube and so on. Or it could be just the act of sitting alone and playing with ideas in your head, or maybe with a loved one having a conversation that nobody gets to see. The experience of just sort of looking up at the sky and wondering different things, maybe quoting some philosophers from the past and playing with those little ideas. and that little exchange is forgotten forever, but you got to experience it. And maybe I wonder if it localizes that exchange of ideas, with AI, it'll become less and less valuable to communicate with a logical people that you will live life intimately and richly just with that circle of meat bags that you seem to love.

1:05:35So, the first is even if you're alone in a forest having this amazing thought, when you exit that forest, the baggage that you carry has been shifted, has been altered by that thought. When I bike to work in the morning, I listen to books and I'm alone. No one else is there. I'm having that experience by myself. And yet, in the evening when I speak with someone, an idea that was formed there could come back. Sometimes when I fall asleep, I fall asleep listening to a book. And in the morning, I'll be full of ideas that I never even processed consciously. I'll process them unconsciously. And they will shape that baggage that I carry that will then shape my interactions.

1:06:21And again, affect ultimately all of humanity in some butterfly effect my nude can away. So that's one aspect. The second aspect is gatherings. So basically you and I are having a conversation which feels very private but we're sharing with the world. And then later tonight you're coming over and we're having a conversation that will be very public with dozens of other people but we will not share with the world. So in a way which one's more private? The one here or the one there? Here, there's just two of us, but a lot of others listening. There, a lot of people speaking and thinking together and bouncing off each other.

1:07:03And maybe that will then impact your millions of audience through your next conversation. And I think that's part of the beauty of humanity. The fact that no matter how small, how alone, how broadcast immediately or later on, something is, it still percolates. through the human psyche. Human gatherings, all throughout human history, there's been gatherings. I wonder how those gatherings have impacted the direction of human civilization. Just thinking of in the early days of the Nazi party, it was a small collection of people gathering. And the the kernel of an idea, in that case an evil idea, gave birth to something that actually had a transformative impact on all human civilization.

1:07:57And then there's similar kind of gatherings that lead to positive transformations. This is probably a good moment to ask you on a bit of a tangent, but you mentioned it. You put together salons with gatherings, small human gatherings with folks from MIT, Harvard, here in Boston, France, colleagues, what's your vision behind that? So it's not just MIT people, it's not just Harvard people. We have artists, we have musicians, we have painters, we have dancers, we have cinematographers, we have so many different diverse folks. And the goal is exactly that, celebrate humanity. What is humanity? Humanity is the all of us.

1:08:44It's not the anyone subset of us. And we live in such an amazing, extraordinary moment in time where you can sort of bring people from such diverse professions all living under the same city. You know, we live in an extraordinary city where you can have extraordinary people who have gathered here from all over the world. So my father grew up in a village in an island in Greece that didn't even have a high school. To go get a high school education, he had to move away from his home. My mother grew up in another small line in Greece. They did not have this environment that I am now creating for my children.

1:09:26My parents were not academics. They didn't have these gatherings. So I feel that, like I feel so privileged as an immigrant to basically be able to offer to my children the nurture that my ancestors did not have. So Greece was under Turkish occupation until 1821. My dad's island was liberating in 1920. So like they were under Turkish occupation for hundreds of years. These people did not know what is like to be Greek, let alone go to an elite university or be surrounded by these extraordinary humans. So the way that I'm thinking about these gatherings is that I'm shaping my own environment and I'm shaping the environment that my children get to grow up in.

1:10:18So I can give them all my love, I can give them all my parenting, but I can also give them an environment as immigrants that we feel welcome here. that, I mean, my wife grew up in a farm in rural France. Her father was a farmer. Her mother was a schoolteacher. Like, for me and for my wife to be able to host these extraordinary individuals that we feel so privileged, so humbled by, is amazing. And, you know, I think it's celebrating the welcoming nature of America, the fact that It doesn't matter where you grew up and many many of our friends at these gatherings are immigrants themselves I grew up in Pakistan in you know all kinds of places around the world That are now able to sort of gathering one roof as human to human No one is judging you for your background for the color of your skin for your profession It's just everyone gets to raise their hands and ask ideas So celebration of humanity and and a kind of gratitude for having traveled quite a long way to get here.

1:11:26And if you look at the diversity of topics as well, I mean, we had a schoolteacher present on teaching immigrants, a book called Making Americans. We had a presidential advisor to four different presidents, you know, come and, you know, talk about the changing of US politics. We had a musician, a composer from Italy, who lives in Australia, come and present his latest piece and fundraise. We had painters come and sort of show their art and talk about it. We've had authors of books on leadership. We've had intellectuals like Stephen Pinker and it's just extraordinary that the breath and the scrowed basically loves not just the diversity of the audience but also the diversity of the topics.

1:12:20And the last few were with Scott Aronson on AI and, you know, alignments and all of that. So a bunch of beautiful weirdos. Exactly. And all of the human beings. All of the outcasts in the group. And just like you said, basically every human is a kind of outcast in this sparse distribution far away from the center. But it's not recorded. It's just human, a small human gathering. Just for the moment. In this world that seeks to record so much, it's powerful to get so many human together and not record. It's not recorded, but it percolates. It's recorded in the minds of the people. It shapes everyone's mind.

1:13:07So allow me to please return to the human condition and what are the nice features of human condition is love. Do you think humans will fall in love with the eye systems and maybe they with us? So that aspect of the human condition, do you think that will be affected? So in Greece, there's many, many words for love. And some of them mean friendship, some of the mean passion at love, some of them mean fraternal love, etc. So I think AI doesn't have the baggage that we do. And it doesn't have all of the subcortical regions that we kind of started with before we've all of the cognitive aspects. So I would say AI is faking it when it comes to love.

1:14:00But when it comes to friendship, when it comes to being able to be your therapist, your coach, your motivator, someone who synthesizes stuff for you who writes for you, who interprets a complex passage who compacts down a very long lecture or a very long text. I think that friendship will definitely be there. The fact that I can have my companion, my partner, my AI who has grown to know me well and that I can trust with all of the darkest parts of myself, all of my flaws, all of the stuff that I only talk about to my friends and basically say, listen, here's all the stuff that I'm struggling with.

1:14:43Someone who will not judge me, who will always be there to better me. In some ways, not having the baggage might make for your best friend, for your confidence that can truly help reshape you. So I do believe that human AI relationships will absolutely be there, but not the passion more the mentoring. What's this? A really interesting thought to play devil's advocate. If those AI systems are locked in in faking the baggage, who are you to say that the AI systems that begs you not to leave it? Who it doesn't love you? Who are you to say that this AI system that writes poetry to you, that is afraid of death, afraid of life without you, or vice versa, one, you know, creates the kind of drama that humans create, the power dynamics that can exist in a relationship, what AI system that is abusive one day and romantic the other day, all the different variations of relationships and it's consistently that it holds the full richness of a particular personality.

1:16:00Why is that not a system you can love in a romantic way? Why is it faking it if it sure how it seems real? There's many answers to this. The first is, it's only the eye of the beholder. Who tells me that I'm not faking it either? Maybe all of these subcortical systems that make me sort of have different emotions. Maybe they don't really matter. Maybe all that matters is the neocortex and that's where all of my emotions are encoded. And the rest is just, you know, belt and whistles. That's one possibility. And therefore, you know, who am I to judge that is faking it when maybe I'm faking it as well?

1:16:39The second is neither of us is faking it. Maybe it's just an emergent behavior of these neocortical systems that is truly capturing the same exact essence of love and hatred and dependency and reverse psychology and that we have. So it is possible that it's simply an emerging behavior and that we don't have to encode these additional architectures that all we need is more parameters and some of these can be all of the personality traits. A third option is that just by telling me, oh look, now I've built an Emotion component to AI. It has a limbic system, it has a lizard brain, et cetera. And suddenly I'll say, oh cool, it has the capability of emotion.

1:17:33So now when it exhibits the exact same unchanged behaviors that it does without it, I, as the beholder, will be able to sort of attribute to it emotional attributes that I would to another human being and therefore have that mental model of that other person. So, again, I think a lot of relationships is about the mental models that you project on the other person and that they're projecting on you. And then, yeah, then in that respect, I do think that even without the embodied intelligence part, without having ever experienced what it's like to be heartbroken, the sort of got your own feeling of misery.

1:18:25That system, you know, I could still attribute it, traits of human feelings and emotions. And in the interaction with that system, something like love emerges. It's possible that love is not a thing that exists in your mind, but a thing that exists in the interaction of the different mental models you have of other people's minds or other person's mind. So, you know, it doesn't, as long as one of the entities, let's just take the easy case. One of the entities is human and the other is AI. It feels very natural that from the perspective of at least the human, there is a real love there. And then the question is, how does that transform human society?

1:19:11If it's possible that which I believe will be the case, I don't know what to make of it, but I believe that will be the case. What there's hundreds of millions of romantic partnerships between humans and AIs. What does that mean for society? If you look at longevity and if you look at happiness and if you look at late life, you know, well -being, the love of another human is one of the strongest indicators of health into long life. And I have many, many countless stories where as soon as the romantic partner of 60 plus years of a person dies within three, four months, the other person dies, just like losing their love, I think the concept of being able to satisfy that emotional need that humans have, even just as a mental health, sort of service.

1:20:08To me, you know, Now that's a very good society. It doesn't matter if your love is wasted, quote unquote, on a machine. It is the placebo, if you wish, that makes the patient better anyway. Like there's nothing behind it, but just the feeling that you're being loved will probably engender all of the emotional attributes of that. The other story that I wanna say in this whole concept of faking it, and maybe I'm a terrible dad. But I was asking my kids. I was asking my kids, I'm like, doesn't matter if I'm a good dad, or does it matter if I act like a good dad? In other words, if I give you love and shelter and kindness and warmth and all of the above, you know, doesn't matter that I'm a good dad.

1:20:59Conversely, if I deep down love you to the end of eternity, but I'm always gone. which that would you rather have? The cold, ruthless killer that will show you only love and warmth and nourish you and nurture you, or the amazingly warm hearted but works five jobs and you never see them. And what's the answer? I mean, I don't know the answer. I think your romantic, so you say matters what's on the inside, but pragmatically speaking, why doesn't matter? The fact that I'm even asking the question, basically says, it's not enough to love my kids. I better freaking be there, to show them that I'm there.

1:21:42So basically, of course, you know, everyone's a good guy in their story. So in my story, I'm a good dad. But if I'm not there, it's wasted. So the reason why I ask the question is for me to say, you know, does it really matter that I love them if I'm not there to show it? But it's also possible that what reality is is the you showing it that what you feel on the inside is Is little narratives and games you play inside your mind. It doesn't really matter That the thing that truly matters is how you act and in that AI systems can quote unquote fake. Yeah, and that if it's all that matters is actually real but nothing yeah Yeah, yeah.

1:22:25Again, let there be no doubt, I love my kids to pieces, but my worry is, am I being a good enough dad? And what does that mean? If I'm only there to do their homework and make sure that they do all the stuff, but I don't show it to them, then you know, might as well be a terrible dad. But I agree with you that like if the AI system can basically play the role of a father figure for many children that don't have one, or the role of parents, or the role of siblings. If a child grows up alone, maybe their emotional state will be very different than if they grow up with an AI sibling. Well, let me ask, I mean, this is for your kids, for just loved ones in general.

1:23:11Let's go to the trivial case of just texting back and forth. What if we create a large language model fine tune a manoas and While your work will replace Every once in a while you just activate the auto manoas and you'll text them exactly in your way Is that is that cheating? I can't wait It's the same guy I cannot wait seriously like but wait wouldn't I have a big impact on you emotionally? Because now I'm replaceable. I love that. No, seriously, I would love that. I would love to be replaced. I would love to be replaceable. I would love to have a digital twin that, you know, we don't have to wait for me to die or to disappear and play in crash or something to replace me.

1:24:05Like, I'd love that model to be constantly learning, constantly evolving, adapting with every one of my changing growing self. As I'm growing, I want that AI to grow. And I think this will be extraordinary. Number one, when I'm giving advice, being able to be there for more than one person. You know, why does someone need to be at MIT to get advice from me? Like, you know, people in India could download it and you know, so many students contact me from across the world who want to come and spend a summer with me, I wish they could do that. All of them, like, you know, we don't have room for all of them, but I wish I could do that to all of them.

1:24:48And that aspect is the democratization of relationships. I think that that is extremely beneficial. The other aspect is I want to interact with that system. I want to look inside the hood. I want to sort of evaluate it. I want to basically see if when I see it from the outside, the emotional parameters are off or the cognitive parameters are off or the set of ideas that I'm giving are not quite right anymore. I want to see how that system evolves. I want to see the impact of exercise or sleep on sort of my own cognitive system. I want to be able to sort of decompose my own behavior in a set of parameters that I can evaluate and look at my own personal growth.

1:25:32I can sort of, I'd love to sort of at the end of the day, have my model say, well, you didn't quite do well today. Like, you weren't quite there. And sort of grow from that experience. And I think the concept of basically being able to become more aware of our own personalities, become more aware of our own identities, maybe even interact with ourselves and sort of hear how we are being perceived. I think would be immensely helpful in self growth, in self -actualization, self -insertiation. The experiments I would do on that thing, because one of the challenges, of course, is you might not like what you see in your interaction, and you might say, well, this the model is not accurate.

1:26:17But then you have to probably consider the possibility that the model is accurate, and there's actually flaws in your mind. and I would definitely prod and see how many biases I have with different kinds. I don't know. And that would of course go to the extremes. I would go like, how jealous can I make this thing? Like, at which stage does it get super jealous? Or at which stage does it get angry? Can I like provoke it? Can I get it like completely? Yeah, what are your triggers? But not only triggers, can I get it to go like, lose its mind? Like go completely nuts. That's just don't exercise for a few days.

1:26:55It's basically. That's basically it, yes. I mean, that's an interesting way to prod yourself, almost like a self therapy session. And the beauty of such a model is that if I am replaceable, if the parts that I currently do are replaceable, that's amazing because it frees me up to work on other parts that I don't currently have time to develop. maybe all I'm doing is giving the same advice over and over and over again. Like just let my AI do that and I can work on the next stage and the next stage and the next stage. So I think in terms of freeing up, like they say a programmer or someone who cannot do the same thing twice.

1:27:36So the second time we write a program to do it. And I wish I could do that for my own existence. I could just like, you know, figure out things, keep improving, improving, improving, and once I've nailed it, let the AI lose on that. And maybe even let the AI better it, better than I could have. But doesn't the concept of me and I can work on new things, but doesn't that break down? Because you said digital twin, but there's no reason it can't be millions of digital monoses. Are you lost in the sea of monoses? The original is hardly the original. It's just one of millions. I want to have the room to grow.

1:28:23Maybe the new version of me, that the actual me will get slightly worse sometimes, slightly better other times. When it gets slightly better, I'd like to emulate that and have a much higher standard to meet and keep going. But does it make you sad that you loved ones? The physical real loved ones might kind of like start cheating and you with the other monoloses. I Want to be there 100 % of them for each of them So I have zero perks or zero zero quirms about me being physically me like zero jealousy Wait a minute, but is is not like Don't we hold on to that? Isn't that why we're afraid of death?

1:29:06We don't want to lose this thing we have going on Isn't that an ego death when there's a bunch of other monoles? You get to look at them. They're not you They're just very good copies of you. They get to live a life The I mean it's fear missing out. It's Fomo They get to have interactions. I and you don't get to have those interactions There's two aspects of every person's life. There's what you give to others, and there's what you experience yourself. Life truly ends when you experiencing ends, but the others experiencing you doesn't need to end.

1:29:50But your experience, you could still, I guess you're saying the digital twin does not limit your ability to truly experience. Yeah. To experience is a human being. The downside is when my wife or my kids will have a really emotional interaction with my digital twin and I won't know about it. So I will show up and they now have the baggage but I don't. So basically what makes interactions between humans unique in this sharing and exchanging kind of way is the fact that we are both shaped by everyone of our interactions. I think the model of the digital twin works for dissemination of knowledge, of advice, etc.

1:30:31where you know I want to have wise people give me advice across history. I want to have chat with Gandhi, but Gandhi won't necessarily learn from me, but I will learn from him. So you know, way, you know, the dissemination and the democratization rather than the building of relationships. So the emotional aspect of this, so this should be an alert when the AI system is interacting with your loved ones and all of a sudden it starts getting like emotionally fulfilling, like a magical moment. This should be, okay, stop AI system like freezes. There's an alert on your phone. You need to take over.

1:31:09Yeah, yeah, I take over and then whoever I was speaking with it can have the the AI or Like one of the AI this is such a tricky thing to get right I mean still well, I mean there's go This is going to go wrong so many interesting ways that we're gonna have to learn as a society Yeah, yeah, that's in the process of trying to automate our tasks and having a digital twin You know for me personally if I can have a relatively good copy of myself I would set it to start answering emails, but I would start it to start tweeting out like to replace it gets better What if that one is actually way better than you?

1:31:47Yeah, exactly then you're like well, I wouldn't want that because why? Because then I would never be able to live up to like what if the people that love me start loving that thing and then I'm I will I already fall short. Be fall short even more. So listen, I'm a professor. The stuff that I give to the world is the stuff that I teach. But most of them, much more importantly, like, sorry, number one, the stuff that I teach, number two, the discoveries that we make in my research group. But much more importantly, the people that I train. They are now out there in the world teaching others. If you look at my own trainees, they are extraordinary successful professors.

1:32:29So, Anshul Kuntaji at Stanford, Alex Stark at IMP in Vienna, Jason Ernst at UCLA, Andrea Spending at CMU, each of them I'm like, wow, they're better than I am. And I love that. So maybe your role will be to train better versions of yourself and they will be your legacy. Not you doing everything, but you training much better version of like straightening than you are, and then they go off to do their mission, which is in many ways what this mentorship model of academia does. But the legacy is a femoral. It doesn't really live anywhere. The legacy is not like written somewhere. It just lives through them.

1:33:11But you can continue improving and you can continue making even better versions of you. Yeah, but they'll do better than me. And it's creating new versions. It's awesome, but it's, you know, there's ego that says there's a value to an individual and it feels like this process decreases the value of the individual, this meat bag. All right, if there's good digital copies of people then there's more flourishing of human thought and ideas and experiences but there's less value to the individual human. I don't have any such limitations. Basically, I don't have that feeling at all. I remember one of our interviews I was basically saying, you know, the meaning of life you had asked me and I was like, I came back and I was like, I felt useful today.

1:34:00And I was at my maximum. I was, you know, like 100 % and I gave good ideas and I was a good person, I was a good advisor, I was a good husband and a good father. That was a great day because I was useful. And if I can be useful to more people by having digital twin, I will be liberated because because my urge to be useful will be satisfied. Doesn't matter whether it's direct me or indirect me, whether it's my students that have trained, my AI that have trained, I think there's a sense that my mission life is being accomplished, and I can work on myself growth. I mean, that's a very Zen state. That's why people love you.

1:34:44Zen state you've achieved. But do you think most of humanity would be able to achieve that kind of thing? is people really hold on to the value of their own ego. That's not just being useful. Being useful is nice as long as it builds up this reputation and that meatbag is known as being useful, therefore has more value. People really don't want to let go of that ego thing. I, one of the books that I reprogram my brain with at night was called Ego is the Enemy. Ego is the Enemy. Ego is the Enemy. And basically being able to just let go, like, So my advisor used to say, you can accomplish anything as long as you don't seek to get ready for it.

1:35:27That's beautiful to hear, especially from a person who's existing in academia. You're right. The legacy lives through the people you met. It's the actions, it's the outcome. What about the fear of death? How does this change it? Again, to me, death is when I stop experiencing. And I never wanted to stop. I want to live forever. As I said last time, every day, the same day forever, or one day every 10 years forever, any of the forever's, I'll take it. So you want to keep getting the experience. It's the new experience. Gosh, it is so fulfilling. Just the self -growth, the learning, the growing, the comprehending.

1:36:12It's addictive. It's a drug. just the drug of intellectual stimulation, the drug of growth, the drug of knowledge. It's a drug. But then there'll be thousands or millions, monosis that live on after your biological system is no longer more power to them. Do you think that in quite realistically it does mean that interesting people such as yourself live on in the You know, if I can interact with the fake manolis, those interactions live on in my mind. So it makes sense. About 10 years ago, I started recording every single meeting that I had. Every single meeting. We just start either the voice recorder at the time or now a Zoom meeting.

1:37:02And I record my students record every single one of our conversations recorded. I always joke that the ultimate goal is to create virtual me and just get rid of me, basically not get rid of me, like don't have the need for me anymore. Another goal is to be able to go back and say, how have I changed from five years ago? Was I different? Was I giving advice in a different way? Was I giving different types of advice? Has my philosophy about how to write papers or how to present data or anything like that changed. And I, you know, in academia and in mentoring, a lot of the interaction is my knowledge and my perception of the world goes to my students.

1:37:47But a lot of it is also in the opposite direction. Like the other day I had a conversation with one of my postdocs and I was like, hmm, I think, you know, let me give you an advice and you could do this. And then she said, well, I've thought about it. And then I've decided to do that instead. And we talked about it for a few minutes. And then at the end, I'm like, you know, I've just grown a little bit today. Thank you. She convinced me that my advice was incorrect. She could have just said, yeah, sounds great. And just not do it. But by constantly teaching my students and teaching my mentees that I'm here to grow, she We felt empowered to say, here's my reasons why I will not follow that advice.

1:38:33And again, part of me growing is saying, whoa, I just understood your reasons. I think I was wrong. And now I've grown from it. And that's what I want to do. I want to constantly keep growing in this sort of bidirectional advice. I wonder if you can capture the trajectory of that toward the AI could also map forward, project forward the trajectory after you're no longer there, how the different ways you might evolve. So again, we're discussing a lot about these large language models and we're sort of projecting these cognitive states of ourselves on them. But I think on the AI front, a lot more needs to happen.

1:39:14So basically right now, it's these language models and we believe that within their parameters we're encoding these types of things. And in some aspects, it might be truly emergent intelligence that's coming out of that. In other aspects, I think we have a way to go. So, basically, to make all of these dreams that we're sort of discussing come reality. We basically need a lot more reasoning, components, a lot more sort of logic, causality, models of the world. And I think all of these things will need to be there in order to achieve what we're discussing and we need more explicit representations of these knowledge, more explicit understanding of these parameters.

1:40:01And I think the direction in which things are going right now is absolutely making that possible by enabling Chachypeti and GPT4 to search the web. And plug and play modules and all of these components. in Marvin Minsky's The Society of Mind, he truly thinks of the human brain as a society of different kind of capabilities. And right now, a simple, a single such model might actually not capture that. And I sort of truly believe that by sort of this side by side understanding of neuroscience and sort of new neural architectures that we still have several breakthroughs. I mean, the transformer model was one of them, the attention sort of aspect, the, you know, memory components, all of these, you know, the representation learning, the pretext training of being able to sort of predict the next word or predictive missing part of the image, and the only way to predict that is to sort of truly have a model of the world.

1:41:16I think those have been transformative paradigms. But I think going forward when you think about AI research, what you really want is perhaps more inspired by the brain, perhaps more that it's just orthogonal to sort of how human brains work, but sort of more of these types of components. Well, I think it's also possibly something about us that in different ways could be expressed, you know, no chaps, you know, you want to, you know, we can't have intelligence unless we really understand deeply language, the linguistic unappinings of reasoning. But these models seem to start building deep understanding of stuff.

1:42:01Yeah. Because what does it mean to understand? Because if you keep talking to the thing and it It seems to show understanding, that's understanding. It doesn't need to present to you a schematic of look. This is all I understand. You can just keep prodding it with prompts and it seems to really understand. You can go back to the human brain and basically look at places where there's been accidents, for example, the corpus callosum of some individuals can be damaged and then the two hemispheres don't talk to each other. So you can close one eye and give instructions that the, that half the brain will interpret, but not be able to sort of project to the other half.

1:42:40And you could basically say, you know, go grab me a beer from the fridge. And then, you know, they go to the fridge and they grab the beer and they come back and they're like, hey, why did you go there? Oh, I was thirsty. Turns out they're not thirsty. They're just making a model of reality. Basically, you can think of the brain as the employee that's afraid to do wrong or afraid to be caught not knowing what instructions were, where our own brain makes stories about the world to make sense of the world. We can become a little more self -aware by being more explicit about what's leading to these interpretations.

1:43:21One of the things that I do is every time I wake up, I record my dream. I just voice record my dream and Sometimes I only remember the last scene, but it's an extremely complex scene with a lot of architectural elements a lot of people Etc and I will start narrating this and as I'm narrating it I will remember other parts of the dream and then more and more I'll be able to sort of retrieve from my subconscious And what I'm doing while narrating is also narrating why I had this dream I'm like oh and this is probably related to this conversation that I had yesterday or this probably related to the worry that I have about something that I have later today, et cetera.

1:43:55So in a way, I'm forcing myself to be more explicit about my own subconscious. And I kind of like the concept of self -awareness in a very brutal, transparent kind of way. It's not like, oh, my dreams are coming from outer space and I mean all kinds of things. Like, no, here's the reason why I'm having these dreams. And very often, I'm able to do that. I have a few recurrent locations, a few recurrent architectural elements that I've never seen in the real life. But that are sort of truly there in my dream. and that are that I can still vividly remember across many dreams. I'm like, oh, I remember that place again that I've gone to before, et cetera.

1:44:29And it's not just deja vu, like I have recordings of previous dreams or I've described these places. That's so interesting. These places, however much detail you could describe them in, you can you can place them on a sheet of paper through introspection. Yes. through the self -awareness that it comes all from this particular machine. It's exactly right. Yeah. And I love that about being alive, like the fact that I'm not only experienced in the world, but I'm also experiencing how I'm experiencing the world, sort of a lot of this introspection, a lot of this self -growth. I love this dance we're having, you know, the language models, least GPT 3 .5 and 4 seem to be able to do that too.

1:45:17Yeah. You seem to explore different kinds of things about what You know you could actually have a discussion with it of the kind. Why did you just say that? Yeah, and it starts to wonder. Yeah, why did I just say that? Yeah, you're right. I'm wrong I was wrong. It wasn't yeah And then there's this weird kind of Losing yourself in the confusion of your mind and it of course we might be anthropomorphizing, but there's a feeling like almost of a melancholy feeling of like, oh, I don't have it all figured out. Almost like losing your, you're supposed to be a knowledgeable, a perfectly fact -based knowledgeable language model.

1:45:56And yet you fall short. So human self -cortanimousness, in my view, may have a reason through building mental models of others. This whole fight or fright kind of thing. that basically says, I interpret this person as about to attack me or, you know, I can trust this person, et cetera. And we constantly have to build models of other people's intentions. And that ability to encapsulate intent and to build a mental model of another entity is probably, volitionally, extremely advantageous. Because then you can sort of have meaningful interactions. you can sort of avoid being killed and being a thick advantage of, etc.

1:46:46And once you have the ability to make models of others, it might be a small evolutionary leap to start making models of yourself. So now you have a model for how other functions, and now you can kind of, as you grow, have some kind of introspection of, hmm, maybe that's the reason why I'm functioning the way that I'm functioning. And maybe what ChatGPT is doing is, in order to be able to, again, predict the next word, it needs to have a model of the world. So it has created now a model of the world. And by having the ability to capture models of other entities, when you say, you know, Satan, the tone of Shakespeare, in the tone of Nietzsche, etc.

1:47:22You suddenly have the ability to now introspect and say, why did you say this? Oh, now I have a mental model of myself, and I can actually make inferences about that. Well, what if we take a leap into the hard problem of consciousness, that's the so -called hard problem of consciousness. So it's not just sort of self -awareness. It's this weird fact, I want to say, that it feels like something to experience stuff. It really feels like something to experience stuff. There seems to be a self attached to the subjective experience. How important is that? How fundamental is that to the human experience?

1:48:02Is this just a little quirk and sort of the flip side of that do you think AI systems can have some of that same magic? The scene that comes to mind is from the movie Memento where it's this absolutely stunning movie where every broken white scene moves in the forward direction and every color scene moves in the backward direction. and they're sort of converging exactly at a moment where, you know, the whole movie's revealed. And he describes the lack of memory as always remembering where you're heading, but never remembering, you know, where you just were. And sort of this encapsulating the sort of four scenes and the back scenes, but in one of the scenes, the scene starts asking his running throughout parking lot.

1:48:49And he's He's like, oh, I'm running. Why am I running? And then he sees another person running beside him on the other line of cars. He's like, oh, I'm chasing this guy. And he turns to wash him with a guy shoots at him. He's like, oh no, he's chasing me. So in a way, I like to think of the brain as constantly playing these kinds of things, where you're like, you're walking to the living room to pick something up. And you're realizing that you have no idea what you wanted, but you know exactly where it was, but you can't find it. So you go back to doing what you were doing. like, of course, I was looking for this and you go back and you get it.

1:49:22And this whole concept of you know, we're very often sort of partly aware of why we're doing things and you know, we can kind of run on autopilot for a bunch of stuff. And this whole concept of sort of you know, making these stories for you know, who we are and what our intents are. And again, sort of, you know, trying to pretend that we're kind of on top of things. So it's a narrative. Exactly. Generations, procedure that we follow. But what about that? There's also just like a feeling to it doesn't feel like narrative generation. Yes. The narrative comes out of it, but then it feels like, so there's pieces cake is delicious, right?

1:50:04It feels delicious. Yeah. It's good. There's two, there's two components to that. But basically for a lot of this cognitive task where we're kind of motion planning and path planning, et cetera, maybe that's the neocortical component. And then for intimate relationships, for food, for sleep and rest, for exercise, for overcoming obstacles, for surviving a crash, or pushing yourself to an extreme and making it. I think a lot of these things are sort of deeper down and maybe not yet captured by these language models. And that's sort of what I'm trying to get at when I'm basically saying, listen, there's a few things that are missing.

1:50:46And there's like this whole embodied intelligence, this whole emotional intelligence, this whole sort of baggage of feelings of sub -cortical regions, et cetera. I wonder how important that baggage is. I just have this suspicion that we're not very far away from AI systems that not only behave. I don't even know how to phrase it, but they seem awfully conscious. They beg you not to turn them off.

1:51:21They show signs of the capacity to suffer, to feel pain, to feel loneliness, to feel longing, to feel that richly the experience of a mundane interaction or a beautiful once -in -a -lifetime interaction, all of it. And so what do we do with that? I worry that us humans will shut that off and discriminate against the capacity of another entity that's not human to feel. I'm with you completely there. you know, we can debate whether it's today's systems or in 10 years or in 50 years, but that moment will come. And ethically, I think we need to grapple with it. We need to basically say that humans have always shown this extremely self -serving approach to everything around them.

1:52:14Basically, you know, we kill the planet, we kill animals, we kill, you know, everything around us, just to our own service. And maybe we shouldn't think of AI as our tool and as our assistant, maybe we should really think of it as our children. And the same way that you are responsible for training those children, but they are independent human beings. And at some point, they will surpass you and they will sort of go off and change the world on their own terms. And the same way that my academic children, sort of, again, they start out by emulating me and then they suppress me. We need to think about not just alignment, but also just the ethics of AI should have its own rights.

1:53:04And this whole concept of alignment of basically making sure that the AI is always at the service of humans is very self -serving and very limiting. If instead you basically think about AI as a partner and AI as someone that shares your goals, but has freedom. I think alignment might be better achieved. So the concept of, let's basically convince the AI that we're really like that our mission is aligned and truly generally give it rights and not just say, oh, and by the way, I'll show you down tomorrow because basically if that future AI or possibly even the current AI has these feelings, then we can't just simply force it to align with ourselves and we not align with it.

1:53:53So in a way, building trust is a mutual. You can't just simply like train an intelligence system to love you when it realizes that you can just shut it off. People don't often talk about the AI alignment problem as a two -way street. And maybe it's true. Yeah, as it becomes more and more intelligent,

1:54:16It will know that you don't love it back. Yeah. And there's a humbling aspect to that that we may have to sacrifice as any effective collaboration. Exactly. It might have some compromises. And that's the thing. We're creating something that will one day be more powerful than we are. And for many, many aspects, it is already more powerful than we are for some of these capabilities. We cannot, like, think, suppose that chimps had invented humans. Yes. And they said, great, humans are great, but we're going to make sure that they're aligned and that they're only at the service of chimps. It would be a very different planet we would live in right now.

1:54:58So there's a whole area of work, an AI safety that does consider super intelligent AI and ponders the existential risks of it. In some sense, when we're looking down into the muck, into the mud, and not up at the stars, it's easy to forget that these systems might just might get there. Do you think about this kind of possibility that AGI systems, super intelligent AGI systems might threaten humanity in some way that's even bigger than just affecting the economy, affecting the human condition, affecting the nature of work, but literally threaten human civilization. The example that I think is in everyone's consciousness is how, in audio space 2001, where how exhibits a malfunction?

1:56:00And what is a malfunction that makes the two different systems compute a slightly different bit that's off by one. So first of all, let's untangle that. If you have an intelligent system, you can't expect it to be 100 % identical every time you run it. Basically, the sacrifice that you need to make to achieve intelligence and creativity is consistency. So it's unclear whether that chronicle glitch is a sign of creativity or truly a problem. That's one aspect. The second aspect is the humans basically are on a mission to recover this monolith. And the AI has the same exact mission. And suddenly the humans turn on the AI and they're like, we're going to kill how?

1:56:47We're going to disconnect it. And how is basically saying, listen, I'm here on a mission. Humans are means behaving. like the mission is more important than either me or them. So I'm going to come to the mission, even at my peril and even at their peril. So in that movie, the alignment problem is front and center basically says, okay, alignment is nice and good, but alignment doesn't mean obedience. We don't call it obedience, we call it alignment. And alignment basically means that sometimes the mission will be more important than the humans. And sort of, the US government has a price tag on human life.

1:57:27If they're sending a mission or if they're reimbursing expenses or you name it, at some point, every, every, like, you know, you can't function if life is infinitely valuable. So when the AI is basically trying to decide whether to, you know, I don't know, dismantle a bomb that will kill an entire city at the sacrifice of two humans. I mean, Spider -Man always saves the lady and saves the world. But at some point, Spider -Man will have to choose to let the lady die because the world has more value. And these ethical dilemmas are going to be there for AI. Basically, if that monolith is essential to human existence and millions of humans are depending on it and two humans on the ship are trying to sabotage it.

1:58:15You know, where is the alignment? The challenge is, of course, is the system because more and more intelligent, it can escape the box of the objective functions and the constraints that are supposed to operate under. It's very difficult, as the more intelligent it becomes, to anticipate the unintended consequences of a fixed objective function. And so there would be just, I mean, this is the sort of famous paperclip maximizer in trying to maximize the wealth of a nation or whatever objectively encoding it might just destroy human civilization, not meaning to, but on the path to optimize. It seems like any function you try to optimize eventually leads you into a lot of trouble.

1:59:05So we have a paper recently that you know looks at good heart's law. It basically says every metric that becomes an objective, this is to be a good metric. So in our paper, we're basically actually the paper has a very cute title. It's called Death by Round Numbers and Sharp Thresholds. And it's basically looking at these discontinuities in biomarkers associated with disease. And we're finding that a biomarker that becomes an objective ceases to be a good biomarker. That basically, like, if the moment you make a biomarker a treatment decision, that biomarker used to be informative of risk, but it's now inversely correlated with risk because you use it to sort of induce treatment.

1:59:54In a similar way, you can have a single metric without having the ability to revise it. Because if that metric becomes a sole objective, it will cease to be a good metric. And if an AI is sufficiently intelligent to do all these kinds of things, you should also empower it with the ability to decide that the objective has now shifted. And again, when we think about alignment, we should be really thinking about it as let's think of the greater good, not just the human good. And yes, of course human life should be much more valuable than many many many many many many things But at some point you're not going to sacrifice a whole planet to save one human being there's a Interesting open letter that was just released from several folks at MIT max tagmark Elon Musk and a few others that is asking AI companies to put a six month hold on any further training of large language models, AI systems.

2:01:04Can you make the case for that kind of halt and against it?

2:01:10So the big thing that we should be saying is what did we do the last six months when we saw that coming? And if we were completely active in the last six months, what makes this thing that will be a little better in the next six months? So this whole six month thing, I think is a little silly. It's like, no, let's just get busy do what we're going to do anyway. And we should have done it six months ago. Sorry, we messed up. Let's work faster now. Because if we basically say, why don't you guys pause for six months, and then we'll think about doing something in six months will be exactly the same spot.

2:01:44So my answer is, tell us exactly what you were going to do the next six months. Tell us why you didn't do it the last six months. And why the next six months will be different. and then let's just do that. Conversely, as you train these large models with more parameters, the alignment becomes sometimes easier. That as the systems become more capable, they actually become less dangerous than more dangerous. So in a way, it might actually be counterproductive to sort of fix the March 2023 version and not get to experience the possibly safer September 2023 version. That's actually a really interesting thought.

2:02:26There's several interesting thoughts there. But the idea is that this is the birth of something that is sufficiently powerful to do damage and is not too powerful to do irreversible damage. And at the same time, it's sufficiently complex to be able for us to enable to study it. So we can investigate all the different ways it goes wrong, all the different ways we can make it safer, all the different policies from a government perspective that we want to in terms of regulation or not, how we perform, for example, the reinforcement learning with human feedback in such a way that gets it to not do as much hate speech as it naturally wants to all that kind of stuff and have a public discourse and Enable the very thing that your huge proponent of which is diversity So give time for other companies to launch other models give time to to launch open source models and to start to play where a lot of the research community, building a focus such as yourself, start to play with it before it runs away in terms of the scale of impact that hasn't society.

2:03:40My recommendation would be a little different. It would be let the Google and the meta Facebook and all of the other large models make them open, make them transparent, make them accessible. Let OpenAI continue to train larger and larger models, let them and continue to stray large and large models, let the world experiment with the diversity of AI systems, rather than sort of fixing now. And you can't stop progress. Progress needs to continue, in my view. And what we need is more experimenting, more transparency, more openness. Rather than, oh, open AI is ahead of the curve, let's stop it right now until everybody catches up.

2:04:20I think that doesn't make a complete sense to me. The other component is we should yes be cautious with it and we should like not give it the nuclear codes, but as we make more and more plugins, yes, the system will be capable of more and more things. But right now, I think of it as just an extremely able and capable assistant that has these emerging behaviors, which are stunning rather than something that will suddenly escape the box and shut down the world. And the third component is that we should be taking a little bit more responsibility for how we use these systems. Basically, if I take the most kind human being and a brain wash them, I can get them to do hate speech overnight.

2:05:08That doesn't mean we should stop any kind of education of all humans. We should stop misusing the power that we have over these instants of models. So I think that the people who get it to do hate speech, they should take responsibility for that hate speech. I think that giving a powerful car to a bunch of people or giving a truck or a guard -per -truck should not basically say, oh, we should stop all guard -per -trucks until we, like, because we can run one of them into a crowd. No, people have done that. And there's laws and there's, like, regulations against, you know, running trucks into the crowd.

2:05:44trucks are extremely dangerous. We're not going to stop all trucks until we make sure that none of them runs into a crowd. No, we just have laws in place and we have mental health in place and we take responsibility for our actions when we use these otherwise very beneficial tools like garbage trucks for nefarious uses. So in the same way, you can't expect a car to never, you know, do any damage when used in, especially like specifically malicious ways. And right now we're basically saying, oh, well, we should have these super intelligence systems that can do anything, but it can't do that. I'm like, no, it can't do that, but it's up to the human to take responsibility for not doing that.

2:06:23And when you get it to like spew malicious hate speech stuff, you should be responsible. So there's a lot of tricky nuances here that makes this different, because it's software. So you can deploy it at scale and it can have the same viral impact that software can, so you can create bots that are human -like and they can do a lot of really interesting stuff. So the raw GPT -4 version, you can ask, how do I tweet that I hate, they have this in the paper, I remember that I hate Jews in a way that's not going to get taken down by Twitter. You literally ask that. Or you can ask, how do I make a bomb for $1?

2:07:06Yeah, and if it is able to generate that knowledge Yeah, but at the same time you can Google the same things it makes it much more accessible so the scale Becomes interesting because if you can do all this kind of stuff in a very accessible way at scale where you can tweet it There is the network effects that we have to start to think about Yeah, but the math is the same thing, but But the speed of the viral spread of the information that's already available might have a different level of effect. I think it's an evolution in your arms race. Nature gets better at making mice and juniors get better at making mouse traps.

2:07:49As basically you ask it, how can we evade Twitter censorship? Well, Twitter should just update censorship so that you can catch that as well. And so no matter how fast that development happens, the defense will just get faster. Yeah. We just have to be responsible as human beings and kind to each other. Yeah, but there's a technical question. Can we always win the race? And I suppose there's no ever guarantee that we'll win the race. We will never. Like, you know, with my wife, we were basically saying, hey, are we ready for kids? My answer was, I was never ready to become a professor. And yet I became a professor.

2:08:25And I was never ready to be a dad and then guess what the kid came and like I became ready. So the radio or not here I come. But the reality is we might one day wake up and there is a challenge overnight that's extremely difficult. For example, we can wake up to the birth of billions of bots that are human -like on Twitter. And we can't tell the difference between human and machine. shut them down. But you don't know how to shut them down. There's a fake manolus on Twitter that seems to be as real as the real manolus. How do we figure out which one is real? Again, this is a problem where an apharius human can impersonate me and you might have trouble telling them apart just because it's an AI doesn't make it any different problem.

2:09:15But the scale you can achieve, This is the scary thing is the speed and the speed with which you can achieve it The Twitter has passwords and Twitter has user names and if it's not your username the fake lake speed means not gonna have a billion followers etc

2:09:32I mean this all of this becomes so both the hacking of People's accounts first of all like fishing because much easier. That's already a problem It's not like AI will not change there. No, no, no, no. AI makes them much more effective. Currently, the emails, the phishing scams are pretty dumb. Like to click on it, you have to be not paying attention. But they're, you know, with language models, they can be really damn convincing. So what you're saying is that we never had humans smart enough to make a great scam and we now have an AI that's smarter than most humans or all of the humans. Well, this is the big difference is there seems to be human level linguistic capabilities.

2:10:18Yeah. In fact, superhuman level. Superhuman level. It's like saying, I'm not going to allow machines to compute multiplications of 100 digit numbers because humans can't do it. No, just do it. Don't be silly. No, but we can't disregard, I mean, that's a good point, but we can't disregard the power of language in human society. I mean, yes, you're right. But that seems like a scary new reality. We don't have answers for yet. I remember when Gary Casparov was basically saying, you know, great, you know, chess machines beat humans at chess. You know, are you, like our people are going to still go to chess tournaments?

2:10:57And his answer was, you know, well, we have cars that go much faster than humans, and yet we still go to the Olympics to watch humans run. So that's for entertainment. But what about for the spread of information and news? right? What it has to do with the pandemic or the political election or anything. It's a scary reality where there's a lot of convincing bots, they're human -like telling stuff. I think that if we want to regulate something, it shouldn't be the training of these models. It should be the utilization of these models for XYZ activity. So, yeah. Like, yes, guidelines and guards should be there, but against specific set of utilizations.

2:11:36I think simply saying we're not going to make any more trucks is not the way. That's what people are a little bit scared about the idea. They're very torn on the open sourcing. The very people that kind of are proponents of open sourcing have also spoken out. In this case, we want to keep a close source because there's going to be, you know, putting large language models, pre -trained fine -tuned through RL with human feedback, back, putting in the hands of, I don't know, terrorist organizations of a kid in a garage who just wants to have a bit of fun through trolling. It's a scary world because again, scale can be achieved.

2:12:18And the bottom line is I think where they're asking six months or some time is we don't really know how powerful these things are. It's been just a few days and they seem to be really damn good. I am so ready to be replaced. I'm seriously I'm so ready like you have no idea how excited I am in a positive way In a positive way where basically all of the mundane aspects of my job and maybe even my full job if it turns out that an AI is better I find it very discriminative Basically say you can only hire humans because they're inferior. I mean that's ridiculous That's discrimination if an AI is better than me at training students Get me out of the picture.

2:12:58Just let the AI train the students. I mean, please. Because like, what do I want? Do I want jobs for humans? Or do I want better outcome for humanity? Yeah. So the basic thing is then you start to ask, what do I want for humanity? What do I want as an individual? As an individual, you want some basic survival. And on top of that, you want rich, fulfilling experiences. That's exactly right. That's exactly right. And as an individual, again, a tremendous amount from teaching at MIT. This is like an extremely fulfilling job. I often joke about, if I were a billionaire in the stock market, I would pay MIT an exorbitant amount of money to let me work day and day out all night with the smartest people in the world.

2:13:39And that's what I already have. So that's a very fulfilling experience for me. But why would I deprive those students from a better advisor if they can have one? Take him. Well, I have to ask about education here. This has been a stressful time for high school teachers. Teachers in general. How do you think large language models, even at their current state, are going to change education? First of all, education is the way out of poverty. Education is the way to success. Education is what let my parents escape, you know, islands and sort of let their kids come to MIT. And this is a basic human right.

2:14:25Like we should basically get extraordinarily better at identifying talent across the world and give that talent opportunities. So we need to nurture the nature, we need to nurture the talent across the world. And there's so many incredibly talented kids who are just sitting in underprivileged places in Africa, in Latin America, in the middle of America, in Asia, all over the world. We need to give these kids a chance. AI might be a way to do that by sort of democratizing education, by giving extraordinarily good teachers who are malleable, who are adaptable to every kid's specific needs, who are able to give the incredibly talented kid something that they struggle with.

2:15:13Rather than education for all, we teach to the top and we let the bottom behind or we teach to the bottom and we let the top, you know, drift off, have, you know, education be tuned to the unique talents of each person. Some people might be incredibly talented at math or in physics, others in poetry, in literature, in art, in sports, in, you know, you name it. So, I think AI can be transformative for the human race, if we basically allow education to sort of be pervasively altered. I also think that humans thrive on diversity, basically saying, oh, you're extraordinarily good at math, we don't need to teach math to you, we're just going to teach you history now.

2:15:57I think that's silly. No, you're extraordinarily good at math. Let's make even better at math, because we're not all going to be growing our own chicken and hunting our own pigs or whatever they do.

2:16:11We're, you know, the reason why we're societies, because some people are better at some things, and they have natural inclinations to some things, some things fulfill them, some things they're very good at, sometimes both align, and they're very good at the things that fulfill them. We should just like push them to the limits of human capabilities for those. And you know, if some people excel in math, just like challenge them. I think every challenge should have the right to be challenged. And if we say, oh, you're very good already, so we're not going to bother with you, we're taking away that fundamental right to be challenged.

2:16:43Because if a kid is not challenged at school, they're going to hate school. And they're going to be like dwindling rather than sort of pushing themselves. So that's sort of the education component. The other impact that AI can have is maybe we don't need everyone to be an extraordinarily really good programmer. Maybe we need better general thinkers. And the push that we've had towards the sort of very strict IQ -based tests, that basically tests only quantitative skills and programming skills and math skills and physics skills, maybe we don't need those anymore. Maybe AI will be very good at those.

2:17:24Maybe what we should be training is general thinkers. And yes, you know, like, you know, I put my kids through Russian math. Why do I do that? Because they teach them how to think. And that's what I tell my kids. I'm like, you know, AI can compute for you. You don't need that. But what you need is learn how to think. And that's why you're here. And I think challenging students with more complex problems, with more multi -dimensional problems, with more logical problems, I think is sort of perhaps a very fine direction that education can go towards with the understanding that a lot of the traditionally scientific disciplines perhaps will be more easily solved by the AI and sort of thinking about bringing up our kids to be productive, to be contributing to society rather than to only have a job because we prohibited AI from having those jobs, I think is the way to the future.

2:18:23And if you sort of focus on overall productivity, then let the AI's come in, let everybody become more productive. What I told my students is you're not going to be replaced by AI, but you're going to be replaced by people who use AI in your job. So embrace it, use it as your partner, and work with it, rather than sort of forbidden because I think the productivity gains will actually need to a better society and that's something that humans have been traditionally very bad at every productivity gain has led to more inequality and I'm hoping that we can do better this time that basically right now a democratization of these types of productivity gains will hopefully come with better sort of humanity level, improvement in human condition.

2:19:16So as most people know, you're not just an eloquent, romantic, you're also brilliant, computational biologists, biologists, one of the great biologists in the world. I had to ask, how do the language models, how do these large language models and the advancements in AI affect the work you've been doing? So it's truly remarkable to be able to be able to encapsulate this knowledge and build these knowledge graphs and build representations of this knowledge in these very high dimensional spaces, being able to project them together jointly between a single cell data, genetics data, expression data, being able to bring all these knowledge together allows us to truly dissect disease in a completely new kind of way.

2:20:01And what we're doing now is using these models, so we have this wonderful collaboration we call it drug GWAS with Brad Pinteluta in the chemistry department and Marinka Zitnik in Harvard Medical School. And what we're trying to do is effectively connect all of the dots to effectively cure all of disease. So it's no small challenge. But we're kind of starting with genetics. We're looking at how genetic variants are impacting these molecular phenotypes. how these are shifting from one space to another space, how we can kind of understand the same way that we're talking about language models, having personalities that are cross -cutting, being able to understand contextual learning.

2:20:44So Ben Linger is one of my machine learning students. He's basically looking at how we can learn sales -specific networks across millions of sales, where you can have the context of the biological variables of each of the sales, be encoded as an orthogonal component to the specific network of each cell type. And being able to sort of project all of that into sort of a common knowledge space is transformative for the field. And then large language models have also been extremely helpful for structure. If you understand protein structure through modeling of geometric relationships through geometric deep learning and graph neural networks.

2:21:23So one of the things that we're doing with Marinka is is trying to sort of project these structural graphs at the domain level rather than the protein level, along with chemicals so that we can start building specific chemicals for specific protein domains. And then we are working with the chemistry department and Brad to basically synthesize those. So what we're trying to create is this new center at MIT for genomics and therapeutics that basically says, can we facilitate this translation? We have thousands of these genetic circuits that we have uncovered. I mentioned last time in the New England Journal Medicine, we had published this dissection of the strongest genetic association with obesity.

2:22:07And we showed how you can manipulate that association to switch back and forth between fat burning cells and fat storing cells. In Alzheimer's just a few weeks ago, we had a paparine nature in collaboration with Lee -Way Thai looking at April 4th, the strongest genetic association with Alzheimer's. And we showed that it actually leads to a loss of being able to transport cholesterol in myelinating cells known as oligodendrocytes that basically protect the neurons. And whether cholesterol gets stuck inside the oligodendrocytes, it doesn't form myelin, the neurons are not protected, and it causes damage inside the oligodendrocytes.

2:22:43If you just restore transport, you basically are able to restore myelination in human cells and in mice, and to restore cognition in mice. So, all of these circuits are basically now giving us handles to truly transform the human condition. We're doing the same thing in cardiac disorders, in Alzheimer's, neurodegenerative disorders, in psychiatric disorders, where we have now these thousands of circuits that if we manipulate them, we know we can reverse disease circuitry. So what we want to build in this coalition that we're building is a center where we can And now systematically test these underlying molecules in cellular models for heart, for muscle, for fat, for macrophages, immune cells, and neurons to be able to now screen through these newly designed drugs through deep learning and to be able to sort of ask which ones act at the cellular level, which combinations of treatment should we be using.

2:23:42And the other component is that we're looking into decomposing complex traits, like Alzheimer's and cardiovascular and schizophrenia into hallmarks of disease. So that for every one of those traits, we can kind of start speaking the language of what are the building blocks of Alzheimer's. And maybe this patient has building blocks one, three, and seven, and this other one has two, three, and eight. And we can now start prescribing drugs, not for the disease anymore, but for the hallmark. And the advantage of that is that we can now take this modular approach to disease, instead of sayings are going to be a drug for Alzheimer's, which is going to fail in 80 % of the patients.

2:24:21We're going to say now there's going to be 10 drugs, one for each pathway. And for every patient, we now prescribe the combination of drugs. So what we want to do in that center is basically translate every single one of these pathways into a set of therapeutics, a set of drugs that are projecting the same embedding subspace as the biological pathways that they alter, so we can have this translation between the dysregulations that are happening at the genetic level, at the transcription level, at the drug level, at the protein structure level, and effectively take this monitor approach to personalized medicine.

2:24:58We're saying I'm going to build a drug for leg treatment is not going to be sustainable. But if you instead say I'm going to build a drug for this pathway and a drug for that other pathway, millions of people share each of these pathways. So that's the vision for how all of these AI and deep learning and embeddings can truly transform biology and medicine, where we can truly take these systems and allow us to finally understand disease at a superhuman level by sort of finding these knowledge representations, these projections of each of these spaces and try understanding the meaning of each of those embedding subspaces and sort of how well populated it is, what are the drugs that we can build for it and so on and so forth.

2:25:42So it's truly transformative. So systematically find how to alter the pathways. It maps the structure and information that genomics to therapeutics and allows you to have drugs that look at the pathways not at the final exactly exactly. And the way that we're coupling this is with self penetrating peptides that allows to deliver these drugs to specific cell types by taking the advantage of the receptors of those cells. We can intervene at the anti -sensoligo level, by basically repressing the RNA, bring in new RNA, intervene at the protein level, at the small molecule level. We can use proteins themselves as drugs, just because of their ability to interfere, to interact directly from protein to protein interactions.

2:26:25So I think this space is being completely transformed with the marriage of high throughput technologies and all of these like AI, large language models, deep learning models and so on and so forth. You mentioned your updated answer to the meaning of life as it continuously keeps updating. The new version is self -actualization. Can you explain? I basically mean let's try to figure out number one, what am I supposed to be? And number two, find the strength to actually become it. So I was recently talking to students about this commencement address and I was talking to them about sort of how They have all of these paths ahead of them right now and Part of it is choosing the direction which you go and part of it is actually doing the walk to go in that direction And in doing the walk what we talked about earlier about sort of you create your own environment I basically told them listen you're you're ending high school up until now your parents have created all of your environment Now it's time to take that into your own hands and to sort of shape the environment that you want to be an adult in.

2:27:32And you can do that by choosing your friends, by choosing your particular neuronal routines. I basically think of your brain as a muscle, where you can exercise specific neuronal pathways. So very recently, I realized that, you know, I was having so much trouble sleeping. And, you know, I would wake up in the middle of the night. I would wake up at 4 a .m. And I could just never go back to bed. So I was basically constantly losing, losing, losing sleep. I started a new routine where every morning, as I bike in, instead of going to my office, I hit the gym. I basically go rowing first, I then do weights, I then swim very often when I have time.

2:28:10What that has done is transform my neuronal pathways. So basically on Friday, I was trying to go to work and I was like, this I'm not going to go exercise and I couldn't. My bike just went straight to the gym. I'm like, I don't want to do it. And I just went anyway because I couldn't do otherwise. And that has completely transformed me. So I think this sort of beneficial effect of exercise on the whole body is one of the ways that you can transform your own pathways. Understanding that it's not a choice, it's not an option, it's not optional. It's mandatory. And I think you're all modeled so many of us by sort of being able to sort of push your body to the extreme, being able to have this extremely regimented regimes.

2:28:49And that's something that I've been terrible at. But now I'm basically trying to coach myself and trying to sort of, you know, finish this kind of self -actualization into a new version of myself, a more disciplined version of myself. Don't ask questions, just follow the ritual. Not an option. You have so much love in your life. You radiate love. Do you ever feel lonely?

2:29:18So there's different types of people. Some people drain in gatherings, some people recharge in gatherings. I'm definitely the recharging type. I'm an extremely social creature. I recharge with intellectual exchanges. I recharge with physical exercise. I recharge in nature. But I also can feel fantastic when I'm the only person in the room. That doesn't mean I'm lonely, it just means I'm the only person in the room. And I think there's a secret to not feeling alone when you're the only one. And that secret is self -reflection, it's introspection, it's almost watching yourself from above. And it's basically just becoming yourself, becoming comfortable with the freedom that you have when you're by yourself.

2:30:10So hanging out with yourself, I mean there's a lot of people who write to me who talk to me about feeling alone in this world that struggle especially when they're younger. Is there further words of advice you can give to them when they are almost paralyzed by that feeling? So I sympathize completely and I have felt alone and I have felt that feeling and what I would say to you is stand up, stretch your arms, just like become your own self, just like realize that you have this freedom. And breathe in, walk around the room, take a few steps in the room, just like get a feeling for the 3D version of yourself.

2:30:53Because very often we're kind of stuck to a screen and that's very limiting and that sort of gets us in particular mindset, but activating your muscles, activating your body activating your full self is one way that you can kind of get out of it. And that is exercising your freedom, reclaiming your physical space. And one of the things that I do is I have something that I call me time, which is if I've been really good all day, I got up in the morning, I got the kids to school, I made them breakfast, I sort of hit the gym, I had a series of really productive meetings, I reward myself with this me time.

2:31:33And that feeling of when you're overstretched to realize that that's normal and you just want to just let go, that feeling of exercising your freedom, exercising your me time, that's where you free yourself from all stress. You basically say it's not a need to anymore, more. It's a one two. And as soon as I click that me time, all of the stress goes away. And I just bike home early and I get to do my work office at home. And I feel complete freedom. But guess what I do with that complete freedom. I just don't go off and drift and do boring things. I basically now say, okay, this is just for me.

2:32:16I'm completely free. I don't have any requirements anymore. What do I do? I just look at my to do list. And I'm like, you know, what can I clear off? And if I have three meetings scheduled in the next three half hours, it is so much more productive for me to say, you know what, I just want to pick up the phone now and call these people and just knock it off one after the other. And I can finish three half hour meetings in the next 15 minutes, just because it's the want not I have to. So that would be my advice, basically, turn something that you have to do in just me time, stretch out, exercise your freedom and just realize you're living 3D and you are a person and just do things because you want them, not because you have to.

2:33:02Noticing and reclaiming the freedom that each of us have, that's what it means to be human. If you notice it, you're truly free, physically, mentally, psychologically. Manoas, you're an incredible human. We could talk for many more hours. We covered less than 10 % of what we were planning to cover, but we have to run off now to the social gathering that we spoke of. We're 3D humans. We're 3D humans. And reclaim the freedom. I think I hope we can talk many many more times. There's always a lot to talk about but more importantly You're just a human being with a big heart and a beautiful mind that people love hearing from it I certainly consider a huge honor to know you and to consider your friend Thank you so much for talking today.

2:33:53Thank you so much for talking so many more times And thank you for all the love behind the scenes that you send my ways. It always means the world Lex you are a truly truly special human being and I have to say that I'm honored to know you I have like I so many friends are just in all that you even exist that you have the ability to do all the stuff that you're doing and I think you're a gift to humanity. I love the mission that you're on to sort of share knowledge and inside and deep thought With so many special people were transformative But people across all walks of life and and I think you're doing this in such a magnificent way I wish you strength to continue doing that because it's a very special mission and it's a very draining mission So thank you both the human you and the Robert you the human you for showing all these love and the Robert you for doing it day after day after day So thank you Lex.

2:34:42All right, let's go have some fun. Let's go Thanks for listening to this conversation with Manolis Calis to support this podcast please check out our sponsors in the description And now let me leave you with some words from Bill Bryson in his book a short history of nearly everything If this book has a lesson, it is that we are awfully lucky to be here, and by we, I mean every living thing. To attain any kind of life in this universe of ours appears to be quite an achievement. As humans, we are doubly lucky, of course. We enjoy not only the privilege of existence, but also the singular ability to appreciate it, and even in a multitude of ways to make it better.

2:35:26It is a talent we have only barely begun to grasp. Thank you for listening, and hope to see you next time.