53: Zhengdong Wang - Feeling the Wave

24:03Are we going to offload most of these evals to the models themselves? This also gets a little into, I was just rereading the Leopold PDF and he gets to the super intelligence harness part. And he's kind of just like, I think we're going to come up with something kind of like RLHF, but like TBD. And like one answer would be to go back to it is like, we want models that are good at creating economic value. And we can kind of measure that based on the hive mind AI of capitalism. But we don't have many other things like that for other types of values.

24:35Zhengdong Wang:Okay, so I'm going to give an overview of my current thinking on this related to RSI, but it's very lightly held. So RSI is even easier than people make it out to be. And then the RSI is... Recursive self-improvement. Yeah, so like getting the AI to specify the evals for itself and things like that. And the artifact that comes out of it, this AGI that does very well on all of these evals, will also be easier than people think. But that once we have that, it won't be what it's cracked up to be. So recently Jack Clark wrote this post that he thinks based on public information that 60 % chance of achieving RSI.

25:21Zhengdong Wang:So achieving this totally end-to-end frontier research, totally automated by the end of 2028. But I think that if we think of all of recursive self-improvement as some kind of spectrum as well, we're like well on the way on this spectrum. And if we just think of it as this is a way to get any eval, like any single number or any bundle of evals up, then it's just like some kind of meta algorithm, some kind of meta search. And while you're working on this, you're kind of procrastinating the question of what makes a good eval. Totally. Yeah, so like... It's sort of like AlphaZero even. Like, it's sort of just like, yeah, we will surely develop the war machine, I don't mean in the violent sense, but like the super algorithm to solve to any endpoint.

26:08Zhengdong Wang:Yeah, yeah. Like, just like this super laser that once you focus it on something, it will be solved. We don't know how to define consciousness. There's all these philosophical questions that we have a hard time specifying. But there's all this like low hanging fruit of like, now researchers spend a lot of time like copy pasting paths or like generating these plots by hand, changing the colors of the lines and things like that. And like all of this obviously could be automated or just like is very, very well within sight, if not done already. So Andre Carpathie's auto research is like a very basic version of this.

26:39On some level, it sort of sounds like you're saying we will have laser beams. And for the most part, it will be people pointing the laser beams at something. But the laser beams are just getting better, stronger, or they last long or whatever. And it sounds like you're a little bit skeptical in the near term of like the AIs knowing where to point the laser beams themselves.

26:59Zhengdong Wang:I think it will happen. I just don't know when and maybe compared to like the optimistic AI researcher. The 2028 country of geniuses in the data center take off all the... Yeah, so I mean on that, it will be like everyone has a country of geniuses in their pocket as well, but that's a different... Yeah, yeah, yeah, yeah. But on the laser beams, yes, I think we have these very high-powered laser beams. I think right now, we, since forever, have had these laser beams that are just human expert AI researchers. Ten years ago, when it was an academic niche, we had a few very high-powered human laser beams that were copy-pasting the checkpoint paths themselves and doing this kind of search themselves.

27:41Zhengdong Wang:and then because the models are general because they really do replace tasks that are very useful to AI research and they're hugely complementary to humans and that's really all you need we're like expanding the number of barrels on the gun and there's just so much to do there's just so many things to try that even with the incredible pace that we're building out compute that talent is joining the field and we're like doubling the number of barrels on the gun, it still won't be enough? Yes, yes, yes. Now we just expand what we want to do, right? We look at all these fields of cognitive work and soon physical work, and we'll be like, okay, so now we need to optimize this for this particular task, for this particular job.

28:29Zhengdong Wang:And you might think in the end, well, none of this is very general, right? You're just sort of brute forcing. Yeah, it's the AlphaGo creativity thing. Yeah, you're searching all possible things. and creativity. Yeah. And at the end of that, you think like move 37 is like the obviously best move. And without having, you know, exhaustively done that search, it looks like a genius to you. But if you had, you know, looked at all the millions of moves, then it's sort of obvious or something. But you do this for like all the spreadsheeting jobs or something like that. And then - Or eventually for invention.

29:03Like part of, again, maybe I'm thinking about this wrong, but like part of the way I'm almost thinking this laser beam metaphor is like, at some point we'll have big enough lasers that you can point the lasers at cancer and you just say like run the search and granted that's not actually one giant tractor beam it's like a million different laser beams of so many different permutations but if you scale it enough

29:23Zhengdong Wang:yeah no no I think it is a good analogy because maybe one thing I'm surprised by I'm not sure how much other people surprised by maybe there are too is like how easy language is or I actually do think a lot of other people would be surprised by this where maybe like an early research agenda. I think OpenAI published it. I don't remember. They had all these bets early on in the company, including RL, including robotics and things like that. And it wasn't so clear that language would be like the first solved. Maybe it would be the last solved. And the thing that we're doing right now, talking to each other in this space of language, it's surprising or could be a little depressing just how predictable all of this is, right?

30:08Zhengdong Wang:That we could do so much of language, like not the best poems, not the best novels, but so much of what we do with language is actually like extremely statistically predictable or just like there's these like connections or we can interpolate between the spaces. And maybe you could say the same about a lot of biology or like this, you know, our human laser beams are just doing like very little jaunts into this big unknown. And there's so much we don't know in the universe. Like there's so, so much we don't know. And this like very powerful statistical tool, like the thing Demis Hassabis says in his Nobel lecture, his challenge is like, I'm sure we'll find a link, but like a classical algorithm will be able to like solve all of these problems.

30:57Zhengdong Wang:Yes. Yeah. If you have a big enough, if you have a galaxy size calculator, most complex problems are just a matter of time and search. Yeah, and we could just be surprised by how simple it is relative to... And we're almost conflating that for this word we call intelligence, perhaps. It'll be like a slightly strange but plausible view on what AI is, which is actually there's no threshold of intelligence and it's just, again, a big enough search, big enough data. Yeah, yeah. So I just think the whole AlphaGo, AlphaFold, this analogy is super, super useful. And it kind of really quickly speed ran through.

31:39Zhengdong Wang:There's pre-training, there's RL. It's this very clean, like, what counts as winning a game, what counts as a value or something like that. And you can just map it on these much fuzzier spaces that humans do. And then maybe at the end of the day, we find that all of the things that we humans do that we think are very complicated. It's actually like an extremely low dimensional statistical thing in the entire universe. And so we have these powerful things that it could just like find all the patterns really fast, interpolate all the spaces really fast. What I'm sort of hearing you imply is that it's very plausible that most of the things we know a lot about and our intelligence itself might not actually be that complicated.

32:21and the universe might still actually be wildly far more competent than you can possibly imagine. Like it's possible AI speed runs us and it still hardly knows anything.

32:30Zhengdong Wang:Yeah, yeah, yeah. And I think Demas does a really good job of like keeping us focused on these stakes of like, you know, this Silicon Valley, like techno singularity kind of where we're going to have Dyson spheres, we're going to have extreme abundance. Like even that is like so small or just like doesn't does pales in comparison to um true nature of reality uh which is like like you we have no idea what's going on in this whole universe and and we have this chance of like um understanding like a a tiny bit like seeing some patterns or like um you know touching the fabric of reality of the the the whole thing and so um yeah we we could we could be more ambitious or uh that's like even weirder it's like uh hard to hard it's humbling and inspiring yeah time uh it's june 2026 i don't know when we'll put this out but probably around around now um and i generally try not to have conversations that are super like of the moment but i think it's worth grounding the time in part because i want to talk about the main theme of your 2025 letter which is i would say it was the probably the first thing i read where i at least very strongly secondhand felt the wave crash over me probably using some of these tools lately um and you basically lay out what you would call your compute theory of everything.

33:48You say, however hard I try, I don't think my descriptions will even move you much. You need to pick your own test. It should be a problem you know well, one you've worked on for years and one you're supposed to be an expert in. You need to predict the result year after year. Then you need to watch AI confound those predictions anyway. Kind of a version of what we were just talking about. Like actually maybe language isn't that hard. I think we are in a different part. We're in a different time than we were even in December when you wrote this. Um, the U S government has started to pay more attention and so on and so forth.

34:21And yet most people clearly still haven't felt the wave. Do you think for every individual person, it's just going to be this kind of thing. Like, do you think there is a macro event that would convince people? Is it getting easier for you to convince people? Maybe a different way of asking the question to use a metaphor using the piece is like, would there be, will there be like a March COVID moment where like in January and February, it was available for people to see, but like, the world didn't wake up?

34:47Zhengdong Wang:Yeah, this is a great question. This is something I keep thinking about all the time, too. So I wanted to write this particular thing for the letter because I felt like it was so hard for me to feel the wave crash over me. And as I mentioned, I maybe have longer timelines than the optimistic AI researcher. So it actually took me five years of full-time being an AI researcher for me to become this AGI pill, so to say. And for this to happen, I had to see so much evidence. And evidence across time, which is that first quote. That's the critical part of it is like, I tried this. Now I saw it be not that good.

35:32Zhengdong Wang:Two years passed. Oh, my gosh. So evidence across time, like repeated instances and tests that I set for myself. So it's not like you're telling me what this test is. You're telling me it's really impressive. It's like, I know this problem. I know it would be impressive. You have finger feel in that problem. Right, right, right. And like, I know like you can't cheat on this in ways that I would know about or something. And that's just like such an expensive way to AGI pill someone. To learn someone. Like you can't expect everyone to, you know, spend five years of their life full time. Or shut down all the schools in the COVID metaphor.

36:07Zhengdong Wang:Yeah, yeah. So there must be some accelerating way of this. Oh, when you're talking about the COVID analogy, I think one thing that we'll do would be like robots or like that's like maybe my upper bound on - Robots walking around. Yeah, yeah, yeah. But not a perfect metaphor, but like I remember the first time I got in a Waymo and I was like videoing the Waymo and I'm like, this is the craziest thing that's ever happened to me. I got into Waymo. 60 seconds later, I was on my phone and I had forgotten. Yeah, so that's a great point. So that also needs to be like repeated instances where you're like, okay, so this week Waymo showed up and then the next week, there's these automated like house building robots that like started building data centers in my backyard.

36:49Zhengdong Wang:You have to be thrust into moving history, perhaps on a repeated sense. Right, right, right. Like it can't just be one instance of moving history. It has to be like, you're feeling the... Right, right. And I think that... countries that have developed really fast in the last few decades. My parents' generation feel this very deep in their bones where they grew up in China. And when they were kids, there was rationing. They had meat once a month or something like that. And now they live in this big suburban house in the U.S. And it's really great. Not to mention you in so many parts of China. Yeah.

37:22Jasmine Sun had this line somebody sent in about the skyscrapers popping up like mushrooms.

37:26Zhengdong Wang:Right, right. Yeah, and there's this picture of Shenzhen 20 years ago, and now it's just like a field. And then 20 years later, there's skyscrapers, and Matt Iglesias tweeted, I bet this really ruined the character of the neighborhood. But that just, living through that over a long period of time, seeing so many changes, that makes you feel it, right? So that's the upper bound of what happened. It is like a fundamental characteristic of humans that we like. You don't see your kid's baby for three months, and it seems like they've grown, like they've doubled in size. Yet the parent doesn't notice it.

37:59This is like a, for better or for worse, we are so good. We might hate change, but we're so good at normalizing change, which makes this jolting hard.

38:07Zhengdong Wang:Yeah. And so, um, I, I really have to credit people who are like way more rational than me, or, uh, you know, a community maybe that, that, uh, is, it was like rationalist to Jason or calls themselves that they're, they're, they're, they were early to the pandemic. Um, they were early to AI. Um, they deserve huge credit for that. And I just, you know, can't get myself to do that. And I had to see so much evidence. And so I really feel this, like, difficulty of, like, I feel very privileged also to be surrounded by people who are, like, very optimistic about AI telling me all the time, trying to convince me of things.

38:46Zhengdong Wang:And then finally, I was like, okay, I've got it. And now I'm, like, you know, some people say, like, off the deep end or something. Was that intellectual or more, I don't know, metaphysical, spiritual? It definitely has to be a combination. So there's this piece of evidence I see for myself. But then you still need someone to handhold you through the rational, like look at the bigger picture, look broadly across society. And then I also tried to do this in the opening to my letter. And I keep trying new ways of doing this. So maybe I'll try now, which is like 10 years ago. is like the Transformer paper not even out yet.

39:25Zhengdong Wang:15 years ago, that was about when deep learning started working that AI could start recognizing cats and dogs. And then just last year, you know, the Pope named himself Leo because of artificial intelligence. And he's like, this is a revolution that, you know, deserves the same kind of shepherding that the first, you know, industrial revolution went through. And that's why I'm going to name myself Leo. And also there's like IMO gold medals, which are like not even impressive now six months into the year. Right. And just that level of change or like going from a small academic niche no one's heard about to the world spending close to a trillion dollars on investment or propping up the economy and things like that.

40:02Zhengdong Wang:And now in more recent still unresolved political news, the federal government realizing some of these models are really cybersecurity dangerous and this thing still not being resolved. right like i i'm just like if if uh if you see this and you're not convinced i'm not sure what would convince you um that that's that's that's one aspect of it um and and looking forward it's like okay so so so maybe maybe um you you've you've you know uh just started reading the news just woken up from a coma you're like okay i i can see that ai is a big thing but but if you had i would argue if you'd woken up from a coma it would be easier yeah yeah yeah yeah this is the thing is that like we're not I'm not referencing I don't know it just came out that open AI 5.6 or GBT 5.6 the government I think is going to be like hand selecting who gets access to it right yeah every individual or something if you showed me that relative to two years ago I would have been like oh my gosh but they just banned or whatever they banned fable that that that's super fair so so I did try to go like um imagine 10 years ago and then and then now but but but But say you see everything now and you're like, okay, I grant that AI is a big deal now, but still maybe bigger than the microwave or something, but not millennium-defining technology.

41:22Or even the internet was a big deal.

41:25Zhengdong Wang:I think we're starting to get to the point, or even the Industrial Revolution. I have a sort of idea in my head that the Industrial Revolution was a big deal. Granted, if I went back and lived it and lived through the change, I would have... So these things are hard in the abstract, which is part of why I ask the question, Is it purely an intellectual thing or something like? Oh, yeah. So, yeah. By the way, on this, I think people should all be history majors. And this helps a bit where, like, as part of the intellectual thing, you go back and you read stuff. And, you know, 100 years ago, there was people still felt like the end of the world was coming, you know, chemical weapons in World War I.

41:58Zhengdong Wang:And there's, like, motor cars everywhere and, you know, societal issues looming on the horizon that you don't know how to solve. And America is only 250 years old, right? It's like people have been just trying to make it work the whole time, and abundance is like a new thing. But on the rational aspect, then, if you look just a few years out in the future, and you grant that the AI becoming a bigger deal has been going on longer than you expected. So maybe one world is like, you see ChatGPT, you see GPT-4, and you think, okay, this is obviously very impressive, obviously beat my expectations, but I'm not ready to sort of just like go full straight line up and to the right on the graph because you're just like more of an empiricist.

42:50Zhengdong Wang:You haven't seen enough data points. Then you just think, okay, maybe it will keep improving for a few generations. But if it plateaued, right, it wouldn't be that weird. And so you're just like waiting for more evidence. If you grant that, like now you could say there's either five years or there's 10 years or 15 years or 70 years of like continual, you know, dots on the plot that keep going up and to the right. Then the rational thing that, you know, I'm trying out to like pill people, it's like how many more doublings do you think we need before this like total physical transformation happens or like bigger kinds of transformation happens.

43:28Zhengdong Wang:And so even if you think the current level of investment is unsustainable, like amount of capex invested or revenue or something like that. We'll just know the answer in the next five to 10 years. Like right now, we're in this sort of compute crunch because we need to build a lot of infrastructure. But even if the rate of growth slows, if it just continues, either AI investment is going to exceed world GDP, which means it's going to have to crash, or we're going to have to grow world GDP because of the AI. Or, you know, this will reach some like crazy form of super intelligence and all this crazy stuff will happen.

44:09Zhengdong Wang:Or there will be some, hopefully not, but some terrible like world historical geopolitical conflict tragedy or something. This is kind of the point you make at the beginning of the piece, though, around the Peter Thiel quote about Elon. For the people who haven't read it, like Thiel's point is that Elon's talking about we're going to have a billion robots. And we're going to have all of these national debt problems. and Teal is critiquing those two things aren't mutually exclusive along the lines of what you just said. Granted, your point is that perhaps we did get the robots and the dad. Yeah, but basically the intellectual side of the equation looking forward is like, I'm trying to tell you like, it's gotten so big now that we can rest easy.

44:49Zhengdong Wang:We will know the answer in the next five years. Like it will either implode or we will enter a new epoch. Like all of us are wondering what's going to happen. Or there are these people who are coping with like, AI is big, but it's going to stay this big, and things don't change very much, or history has ended. So things just generally... Yeah, nothing ever happens. Things just generally stay the way things are. And I'm like, the Financial Times chart where one line is going up and one line is going down, we'll just know the answer. It's gotten big enough to where this will happen very soon, and so it's very exciting.

45:28Zhengdong Wang:And I don't think it takes that much of a leap of once you accept that AI is like a real thing today and that it has changed a lot in the last few years. That, yeah, we'll just know what happens. It's sort of like knowing like a pandemic level event is on the horizon. We just don't know if it will be very good or bad. I don't think that's going to inspire much confidence in people, that last line. Right, but maybe this exercise is just to get people convinced about the moving history. Yes. Well, so there's one line in the piece that I think is really poignant. You say at one point that the curve is exponential.

46:07So if it happens, it doesn't matter when. And then you go on to say, what does it matter if it's two or 20 years away? The only change that's mattered to my AI timelines is that I used to think it wasn't going to happen in my lifetime. And now I think it is. Can you talk about how that has most, that view has most changed your research, the way you think? That cut on what you just said would say, we're not going to have the debt implosion thing, or we're not going to have the economic implosion thing in the next five years. We are going to like, it's going to happen. We're moving up the exponential.

46:39If we are moving up the exponential at all, like we're going to clear the jump maybe. But why is that framing of it? I mean, obviously on one sense, it's just, fundamental and that you're going to get to live to experience it but i think there's a subtler frame on it which is that like if we're on the exponential

46:59Zhengdong Wang:it's uh it's not slowing down like yeah um maybe i would think about it and and and this is like extremely relevant for like everyone's like personal life whether or not you're in tech whether or not you're in the eye um just like granted the two or 20 matters the two or the 20 years like that is a big difference it definitely matters but but but overwhelmingly most important of all is like um both are are you on the exponential or not do you recognize that or like if if you can just do something to uh you know like like tie your ship to the exponential versus um just just like just like knowing it it's like you you you just probably broader make um like better decisions or something like that well so sorry to interrupt but like that is i think that's quite an interesting question which is one one other meta reason why people aren't able to feel the, or aren't feeling the wave crash over them is even if I do look at the math, which is just look at the scaling laws, like the root point you make over this whole piece is that we're on this like long journey, maybe arguably back to Moore's law or even further, which is just like, do the math.

48:00Um, one reason perhaps that we don't feel it is I'm like, what the heck am I supposed to do with the fact that I'm, what does hitching your, your wagon to that, hitching yourself to that wagon? What does that even mean? Like go work in AI? Does it?

48:15Zhengdong Wang:Yeah, I think like any of these specific things are probably going to be wrong. And I was talking to a friend about, you know, like there's one term 19 uncertainty, but I like better the Donald Rumsfeld, he goes up to the podium and he's like, there are no knowns, there are known unknowns, and there's unknown unknowns. And then in the unknown unknown situation, you really don't know what the optimal strategy is. So based on just like some deep preference you have, you might be like extra greedy or extra risk averse. But both of those seem just as good to me. I just think that, yeah, maybe within AI worlds, when we're convinced that this is going to be a big deal, we spend a lot of time talking about, is it going to be two or 20 years?

48:58Zhengdong Wang:Which, like you said, it's super important. It will like totally change like how society is able to adapt well to it or not. But then for someone else, like, or maybe kind of like the defaults, like haven't really thought about it reaction is just okay i just really hope this doesn't happen or something like that but um but but maybe if you if you look at all the beliefs you have or or which conclusion you draw if you just like look at the evidence and and apply your own you know priors to like how you would weigh the evidence um you might come to the uncomfortable conclusion of like um this will happen uh in the next 20 years in the next 50 years just like in just like sometime in your lifetime right and and it definitely matters when but um i i think i think it does give a lot of clarity to to things like i was mentioning uh uh it just like accelerates you asking the question of what do you value yes um and so uh now you could say um okay um if if you're like a young person i need to get a job i need to save enough money i need to um you know figure out a bunch of things um in in my life right and then um when when you're young you think you're gonna to live forever and you never really think about the longer term things.

50:04Zhengdong Wang:But I think the fact that this phenomenon exists, even if it hasn't really physically affected your life at all, you're like totally far away from AI world or something. This is sort of like telling you there's going to be like a pandemic level of change in your lifetime. Totally valid question. What am I supposed to do about that, right? but um um maybe one thing is just like just just uh it's it just becomes a lot easier to stop caring about the petty things because um you're like i've uh yeah i've i've just um received this uh this prognosis of like yeah things are just going to be very different in five years you're going to look back and you're going to be like i i wish i i wish i didn't care so much about um you know uh what other people thought of me or i i wish i you know spent more time with my friends or something like that.

50:52It does feel on something. The more I think about this, it does feel on some level, like if I told you you were going to die in a year or anyone, they were going to die in a year, especially if they were under the age of 80. Yeah. I suspect they would really change their behavior. If I told you you're going to die in three weeks, like, but if I told you you're going to die in seven years, like, yes, intellectually, I think I would versus 40.

51:12Zhengdong Wang:Yeah. But like there is, we're really bad. Yeah. Letting abstract, remotely far away things, letting the wave crash over us? Perhaps a question would be that... And unfortunately, I think this is a really good analogy, and I'm just really desperately trying to find the positive versions of these analogies. There's like, you receive a terminal... Yeah, it's not necessarily death. Yeah, you receive a terminal diagnosis slash the whole of society goes through a pandemic. But I'm like, but... But, you know, I really do believe that AI is going to go well, or I think it's way more likely to go well.

51:50Zhengdong Wang:than not. And so while these analogies like work really well because they really hit on some like sense of urgency or make you feel like the stakes, that sort of thing. The kind of like, imagine you know you will win the lottery in like next year or something like that. Or like - Yes. But even that, by the way, if I was going to win the lottery in three weeks, my behavior would be very different than if I knew I was going to win. Right, right, right. And so the key to like finding such an analogy, like you as an individual winning the lottery or like society uh as a whole winning like a society-wide lottery this kind of like um how to how to make that more compelling or how to communicate that i i think i think the whole field is is is also struggling with this where like where where like the the the uh bleak things just like um you know hit hit home uh more in some way unfortunately um but but yeah like whatever you would do there it's like um yeah imagine imagine you're going to be fabulously wealthy in a few years.

52:52Zhengdong Wang:Like you said, you would be acting very differently or you would receive some kind of new clarity about what you care about, what you value, or you would just know like, oh, I need to really quickly start thinking about what I value, like what makes me human, things like that. I think the labs have achieved this. That's why they're starting all these organizations thinking about all of this, right? The transition and also also after the technology is more stable. One kind of major implication of this is that the people who do know this, who have this secret or not so secret, people working in AI, whatever, need to be better at talking about it.

53:30It's clear that that's something you think a lot about, both in your personal writing, as well as what you kind of urge people on. There were two quotes that I picked out on this that I liked. The first, you say, some people are quick to disavow themselves from doomers or accelerationists. But what else is on offer? Not much if research engineers continue to see myth-making as a chore, second class, a lesser use of their time to quote-unquote real technical work. They will keep working in a world under myth. They keep complaining is inferior. And then slightly more fun, you quote Tolkien as he says, fantasy is a natural human activity.

54:11It certainly does not destroy or even insult reason. And it does not either blunt the appetite for nor obscure the perception of scientific verity. On the contrary, the keener and clearer is the reason the better fantasy will make.

54:29What makes for good myth maybe to start?

54:32Zhengdong Wang:Yeah. I think there is a really good myth specifically for people who are likely to become AI researchers, right? Like all these labs, they have lots of very talented people working for them. And they could, you know, I don't know, go into finance and make a lot more money or something like that. But partly because it's like the other mission-driven people, but like the mission. And the mission of whether it's, you know, touching the fabric of reality, understanding the true nature of reality, or it's impacting a lot of people's lives, like curing cancer and eliminating poverty, hopefully eliminating inequality, all of these.

55:14Zhengdong Wang:That's like a myth that's like, in a good way, a mission that really drives people that would make people - In part, it's such a strong myth, perhaps in part, that it could be part of why these people aren't thinking about that much myth-making otherwise, because it's just like so intrinsic and obvious to us. it's so catnip-y to a certain kind of person. They're just like, how could you care about anything else? This is the most important thing. Yeah, exactly. And also, you know, the myth of like, oh, you are on the Manhattan Project. You are Oppenheimer. You are contributing to this world historical event individually.

55:51Zhengdong Wang:That also works. So I think in that way, the myth-making is going quite well. It's just that this is definitely too simplistic of a view that there's not enough understanding of the diversity of the fantasies that would appeal to more people or that more people have. Maybe it's something like that. Maybe it's something like change is just really uncomfortable because uncertainty is really uncomfortable. And just generally, people don't really like uncertainty. So maybe the kind of find the perfect myth or find the Steve Jobs for AI is kind of just like a really hard problem or really hard to do.

56:32Zhengdong Wang:That could be part of it. I think it's definitely, yeah, worth working on and thinking about though. And that right now, the best myths are directed at the people most likely to receive it. And then you receive it, you might join AI as well as AI becomes bigger. It becomes more inclusive, more pluralist, more normal, so to say. Um, two, two questions. Number one would be in that quote, you, you reference, um, doomers and acceleration risks and what else is on offer. I don't think you're a doomer. I feel pretty confident on that. And maybe you're an acceleration is by some definition, certainly to a normal person.

57:16Um, but I don't get the sense that you're like a pure accelerationist. I think you're working on this in part because you think it's the most important thing. Um, do you have a sense of other narratives that are on offer?

57:28Zhengdong Wang:Yeah. So, so this quote, uh, was from a couple of years ago, right? Yeah. So I think, I think that that was the year where, um, maybe like E-Ack was coined or something like that. And then, and then, uh, uh, in, in, in my mind, that was the year like newspapers starting to started to use the word doomer. And so, um, I chose those two as like, these are like the most prominent myths of, of the time. Um, but they are kind of, I mean, Yeah, they're like definitely ingrained in the water still. I think there are new myths, more complicated ones being developed. I would agree with you. I think if I had to choose between these two ends, I would say I'm more of an accelerationist because I think it will go well.

58:12Zhengdong Wang:And in the same way, I'm trying to find an analogy that's like positive. I think, you know, you should really focus on the solving cancer like 10 years earlier kind of thing being like really good rather than the kind of trying to avoid some bad thing that you think will happen earlier. But these myths have also gotten more inclusive. And so there's like different strains of accelerationism now, right? The second part of my question is going to be, you've also spent time, as I understand it, with a number of people who are closer, for a better way of putting it, closer to the policy side of the world.

58:48I think certainly in the UK and maybe also in the US, do you have a sense of what types of myths or stories or even just simple messaging have been or will be most resonant or clarifying for those people? I mean, it feels more relevant than ever, at least in the US. And some of it's about persuasion, but some of it's just actually about like, I'll let you decide how you want to react to this. You might be anti, but I need you to feel the wave. You make some point somewhere. and granted, I don't think this was that recent, but it wasn't that long ago either, that like there's a few people in the Trump administration, a few people in Saudi and maybe like a couple other senior politicians in the world who have felt the wave.

59:31Zhengdong Wang:Yeah, not my point, but I was quoting someone else. Okay, I'm sorry. Yeah, so I think that one, like there's like two maybe reassuring things. One is this has not really changed in the thing I wrote where I cited this person. like you you should you should frame it as like we are keeping a promise that we previously made and um you know the the way we're keeping it or the technology that we use to keep it is is different but but broadly like um um we have a promise that is the social contract and um uh we will uphold it by uh you know distributing the benefits of this technology to everyone make sure no one's left behind but uh fundamentally the important stuff has has not changed like um you you know, you're living our life, you got a new house, but you know, you're everyone is still going to get a house have there's your the change will not be will not be so disruptive that or so uncertain that you need to really worry deeply.

1:00:29Zhengdong Wang:And the second thing that could be reassuring is volatility is good. Good. We've always had we've always had change and you know, change, change has always been good. And this is like, you grow up in a country with like 10 % GDP growth for like over decades. And you just watch, you know, where you live turn into like a field, into like skyscrapers. And all of a sudden you have like these really fast bullet trains or something like that. It's like, yes, there's a lot of change, but broadly overall, it's good for you. And I think it works for America too. Like America, only 250 years old. you look at like some guy who's alive today and they're like you know just like three generations back was like ninth president of the United States or something like that it's just not that much time and for most of American history so much change right it's like so much happened for most of American history America was not like the global superpower right and so that's a lot of change and telling this myth where you are empowered to make this change or benefit from this change.

1:01:41Zhengdong Wang:It was like, we would hate it if we had an extremely classist society where nothing ever changed and you're just kind of stuck in whichever social standing that you have. But in a world, you're part of a country of very dynamic people who are starting businesses and doing all this cool stuff. And you're making the change yourself. and then you will benefit from this change, like as has happened for all of history. And in fact, it's part of your national identity that, you know, as like a person of this country, you're like really good at adapting to change. And like change has always been really good for you.

1:02:18Zhengdong Wang:I think that could be reassuring as well. Currently, it certainly seems that there is something structural about AI and maybe just modern kind of techno capitalism that is creating a smaller and smaller group of really powerful actors. Maybe a different cut on this would be like, that's one justifiable concern. There's a different take you have somewhere. And I think you're kind of referencing somebody else's idea, but it's the person who's talking about the French Revolution versus the replacement of the English monarch. And it's almost like, it's definitely a little Machiavellian or something, but it is an interesting sort of like way to think.

1:02:57Like for whoever's trying to change the world, you best keep some of these promises. You say, I think this is you, the AI industry has all kinds of French revolutionary tendencies and our own self-conception were bold, inevitable, and on the right side of history. At our worst, we're ignoring our inheritance to remake the world from abstract rational principles, dismissive of accumulated experience, and impatient that no one else is keeping up. I think we're meeting a resistance to that impulse that is earned. Yeah.

1:03:25Zhengdong Wang:Yeah. So if I could go back to my classic cough out answer of like both have to be true at the same time. Yeah, please. It's like, well, I really believe in like competition being good. And if you want to prevent, you know, like really serious like power concentration, there just needs to be a lot of competition. So a lot of unpopular decisions that labs have made, you know, people complain about them. maybe they made these various decisions because they feel like they're in a position of strength and they're like, you know, we think this would be best to do with the models and if we do this, you know, the market can't do very much about it so we're just going to do it.

1:04:06Zhengdong Wang:But then because there's competition, maybe that gets walked back in the end. Maybe labs would do like other things that they're not doing such as, we're just going to, you know, develop this RSI, AJI thing by ourselves and like just keep all the innovations to ourselves, right? but because there's a market that's not going to happen. Or there's a lot of competition between different models. So one company's idea of what is moral and good and how much to defer to the user versus how much input the model should have to the user, the model telling you something is wrong or something. All of this, I think, competition is generally good.

1:04:45Zhengdong Wang:But then, of course, that means It's like, maybe this pulls the future closer to us a bit faster. And you're like, wait, but wait, that's bad. Both are kind of need to be true and happen at the same time. So, yeah. I appreciate you modeling through this with me. I mean, part of the meta thing that I think I'm feeling as I've been thinking about this and through this conversation is just like, it's all further case to be made that the more we can make more, a wide, a plurality of different types of people, Americans, whatever, politicians, whatever, to feel the wave and thus really deeply engage with this.

1:05:25There's a tension there, of course, because one response to that might just be like, we need to stop the AI. But the best possible future to me seems roughly like as many influential and regular people as possible care about this stuff. They have the optimistic understanding of what the technology is, but they also aren't just putting it off as this pie in the sky thing to say like we have two to 20 years to solve some of these problems and it's going to take the whole

1:05:53Zhengdong Wang:gang to like really yeah no but but what we should focus on it it will take the whole gang like uh you know all the labs i i think are um extremely sincere and well-intentioned of like um what what we know is that it's going to be nuts um and you know we're not professional economists yes uh well some of us are not as many as like the whole field of of economics or the whole field of philosophy or the whole field of, you know, whatever it would make to go well for like all these different areas of human inquiry. And we're just kind of like creating these things to like these organizations to like think about these questions because they are important questions.

1:06:36Zhengdong Wang:But yeah, some kind of main goal is to like get more people into this project and we'll take the whole game. And if you don't like that, big tech is deciding all these things, then you... Get involved. Yeah, yeah, yeah. And you can't consistently hold that this AI thing is a scam and also like, oh, please stop disrupting my field. Yes, yes. Amy, just briefly, I know we briefly touched on it, but why aren't you a doomer? So I think I am still more of an empiricist And therefore, there are a lot of risks I do worry about. And maybe this requires a definition of Doomer. But yeah, a lot of the risks are very, humans are very involved in them, like malicious humans using the AI for bad purposes, I think generally characterizes the risks I worry about.

1:07:38Rather than the paper clipping, whatever, we lose control scenario.

1:07:41Zhengdong Wang:And some other general assumptions I'm making are like there will be competition or there is just going to be a lot of degrees of freedom for a lot of different things that you can't predict ahead of time to happen or avenues of these threat vectors. And so given that we live in this very decentralized world, that we've made choices in society to support the benefits of the decentralized world, then you really need to lean into it. And so if it is a spectrum of accelerating versus slowing down, then I think most people are good. Most people are not malicious. And of course, there's offense-defense balances.

1:08:26Zhengdong Wang:But the kind of solution that what I imagine a vague definition of Doomer would support, I feel like would be counterproductive. And yeah, I'm not at all saying the risks aren't real. I'm saying I put a much greater weight on these more human being involved kind of risks. and that the best solution to them, like I wrote in the piece responding to Dara's piece, is very decentralized, a lot of good people in a very decentralized way, thinking about the solutions to this. Yeah, there's a cut on this that's sort of like the cost of progress and the cost of liberty is some risk. And we have taken that trade for a long time and it has paid off really well.

1:09:20Zhengdong Wang:And I would add that the non-liberty is a bigger risk. Yes, yes. One last thing on this, a quote I liked, and maybe just another opportunity for the wave to crash over people a little bit, on like compute and scaling. You say the biggest mistake people make when they make the case for AI is that they say it's different this time. It's not different this time because it's always been different. There hasn't been any constant normal trend ever. and all we've done is be optimistic that we'll muddle through. Nothing is truly inevitable, certainly not progress and progress too might stop tomorrow. All things considered though, it would be stranger if it did than if it didn't.

1:10:02Perhaps you even make this point, but I couldn't help reading this thinking about like, not only does this apply to scaling laws or possibly even computing and Moore's law, but like maybe all of human progress, maybe even the trend of complexity in this little corner of the universe that we're in. you also noted your frustrations with the foundation series speaking of determinism how do you think given maybe a quote like that which is holding a lot how do you think about on one hand the sense of inevitability or determinism and also will or agency

1:10:38Zhengdong Wang:so both are true at the same time but more seriously it's like well when you look at the trend of like 2 % GDP growth for, you know, since we invented invention or something like that. And if you zoom in really closely and you look really closely, it's like all these people trying very hard and doing very different things every time and very weird things every time. And then only when you zoom out, it looks like we call it a law. Yeah, yeah, yeah. And so also, if you believe that AI is general in some way or is like extremely complementary to humans in some way. It's like these human laser beams that we're focusing on problems.

1:11:19Zhengdong Wang:And as like a general law or a general rule, we know that if we focus this human laser beam on this problem for some amount of time, we're going to get something out of it. And of course, it's not guaranteed. It's like probably you're just like rolling dice or something. But probably you put enough laser beams, humans, on something, you get something out of it. We even see this with things like the space race in the 60s or COVID vaccines. Like there is something about human... We put the tractor... And individually, too. Like, you know... Yes, will the power, yes. As a researcher or as a creative, you're like, oh, damn, like, am I really going to be able to think of a next piece?

1:11:54Zhengdong Wang:But if you just, you know, block aside like 10 hours, you're going to get something out of that 10 hours. Destiny is the mother of invention. Yeah, it's going to be a bit more than you expected, a bit less than you expected. But in that way, everything is different. Everything is like... It could definitely be zero. So that aspect is like extremely contingent um not determined um and then when when you zoom out uh it it looks more determined um but but then but then you know like it's it's both like determined and also contingent um the the thing about the the um foundation series is like i i just think there's like no character development in there because there's like these hundreds of years of time jumps and so you only get like a character for like a chapter or something like that and um the i think the idea is very cool and very important and um um uh like a science fiction book should should like really lean into it's like one idea right like i think it's um hugely impactful that uh and and it may be captured like like something about the time it was written in as well that um people imagine like oh we have like newton's laws we we're like discovering all sorts of laws maybe we'll we'll discover like laws to everything right and and that's like also a very old idea and to to have like a work of fiction that really explores that is like really great.

1:13:10Zhengdong Wang:So I'm not like anti-foundation just because it has that idea. I think that relies on the reader to, you know, not read that and totally be like, like go off the deep end on that end of like, you read that and you're like, okay, well now I'm going to discover like the true law. But it's like a data point that you take in your own inner, like balanced everything is true sort of like idea of like um yeah that's that's just like uh another another um character in the pluralist universe i want to talk about personal implications or where we might be going in the era to come first of all similar note to what we just spoke about um i wanted to read two excerpts first from your 2025 letter uh you say later you'll think who could possibly compete?

1:14:01How could your cleverness be worth anything more than a hill of beans against an artifact that cost millions and concentrates within it the cleverness of billions of humans? How arrogant to think yourself clever enough to outpace a factor of a thousand than another thousand than another thousand. This is what they mean when they say general purpose technology. Perhaps a slightly wordy, but I think very good articulation of the super laser beam. Meanwhile, in your 2022 letter, the first one at least available to me, there's a slightly different tone, I think. You say, some people think that there are few, if any, scientific breakthroughs remaining.

1:14:42They think research progress is hard to measure. Ideas are getting harder to find. Maybe all the good ones have already been had. Maybe some extant thing is all you need. I wouldn't be so sure. Marvin Minsky, luminary of our field, predicted, quote, within a generation, the problem of creating artificial intelligence will substantially be solved. End quote. That was in the late 60s. He joins a distinguished class, Lord Kelvin in 1897. Quote, there is nothing new to be discovered in physics now. All that remains is more and more precise measurement. End quote. Cicero reported that Aristotle thought he had just about completed philosophy and that it would surely be completed a short time after his death.

1:15:18Don't be them. Here, actually, take the long view. we're coming back to it over and over again um but there is a paradox there and one is empowering to the human spirit and the other is like deeply deeply humbling if not kind of disappointing or even sad um maybe the best way to ask the question would be do you still believe in the zengdong of 2022 yeah i i can see the the tension there um but i think it

1:15:48Zhengdong Wang:is consistent in the um reason why you are trying to be clever when you do the research and when you're trying to compete against the models um where uh if you're just doing it for like some instrumental purpose like like we do in a lot of the things we do in daily life and errands and for our job it's like we need to get this thing done and here are the things that we do uh to get there and in a job you might think like oh i'm just like having a blast like every day doing this thing right um and that's that's like all that can all be consistent and all be great in that um if you want the the end goal itself uh then you can use a tool to like accelerate the middle part that maybe you don't care so much about and reach the end goal but but let's say um in in terms of like software engineering you you also uh like the process itself right like you you like the puzzle solving aspect of the engineering.

1:16:39Zhengdong Wang:Maybe it is a bit disheartening that you don't find it as useful to other humans when there's this tool that could do it, right? But that one, you can still like explore this kind of puzzle solving aspect yourself in the same way that like athletes do or like game players do. Autotelic. Yeah. Games being a very like self-imposed limitations kind of like can I solve these problems within these limitations kind of thing or like as an artist and now you can do like software engineering as an artist or something like that. And the other aspect that I think is new that's more consistent with the earlier like more human empowering thing is both that there's just so much stuff to do and that part of my earlier answer about getting AGI will not be what it's cracked up to be is that yeah if you just think of like the amount of things we will demand or the amount of things that we will explore like just how big the universe is and how weird it is there will always be something to do and scarcity in the definition of like will the cost be zero will we really have infinite of it we won't reach that we'll just do everything faster we'll like do more things get even more niches and like write even more you know fiction or something like that and create even more universes for ourself um the second way that uh uh there will always be stuff to do is um just like something being very personal so um everything about you like uh you maybe like to do puzzles or you like to create this sort of art um just the fact that you are doing it yourself um is is also very new so like whether you do it with ai or you do it by yourself or um people are fans of your work just because it is you right right now uh friends will read your stuff because they want to know what you think like they want to know your favorite flavor of ice cream not the not the llm's um objective optimal best flavor of ice cream and many people have written about this as well um and so uh the the the personal stuff is is always like your domain is going to be new um and uh scott alexander i think has written a uh a sort of like a like a like a very um um a good good post or like that that makes you feel this particular wave crashing over you of like imagine uh in the future if there are like people in other galaxies and they think they they like read all the history of like what what what was the the creation of powerful ai like and they're like every single character that was like even marginally uh related it's like a celebrity like oh this was their favorite form of ice cream this was like a blog post they wrote um and and it reminds me of uh uh uh in in in the bible the the first like european convert to Christianity.

1:19:23Zhengdong Wang:Her name is Lydia and she's like just remembered forever because she's just like living her life and is like part of this like world historical story. So the personal is new. There's just infinite demand for everything. There's only some particular things that maybe because they're accelerated by tools or something, you would do it differently. But I just see everything as like expansion of options available. i agree with much of that and yet part of the implication in that 2022 quote i think is about like doing things of substance and granted i think relational life is of substance but um in the abstract sense or the grand sense it would be like discovery research like truly getting closer to know in some sense there is like a humbling in a positive way the idea that actually we know 0.00001 % of what there is to know.

1:20:24We can know so much more. But that isn't really something you mentioned. And then I guess at a more local level, most people aren't going to discover scientific theorems or whatever. I do think there's just a sense that for many people, it's hard to have meaning without some kind of meaningful work. So I'm curious how you would take those two on top of what you said.

1:20:43Zhengdong Wang:Recently, Rebecca Lowe wrote this blog. she's a philosopher about um um you know some broader definition of work where um this uh idea of like replacing jobs like but but what even is a job and and i think um um she she i she and i would agree with you that like everyone needs to have some kind of purpose like um um maybe maybe it's just relationships but maybe it's not just relationships and you just need to uh feel like you you are doing something that you find meaningful or you are contributing to like something larger than yourself, like community or like a bigger project or something like that.

1:21:17Zhengdong Wang:But I think that that can be very broadly defined. And I'm curious if you think that people's idea of that can change or not. So maybe with the invention of some tools for agriculture or for making clothes or something like that, like previously our culture would place much higher weight on like being able to hunt or being able to farm or like there's something real about like waking up early in the morning and doing doing this like work that's like real work and maybe maybe even today we we like idealize this this idea of like real work instead of like um you know spreadsheets or something i was literally i was at dinner last night what one of those open kitchens and i was like wow be kind of cool to to do work in a kitchen for a little while like so they they were building a uh apartment building um next to next to uh the the office a few years ago.

1:22:04Zhengdong Wang:And a colleague and I would joke like, you know, we're just like coding. But if you want to see any real engineering happen, just like look out the window. I think I agree. And yet, like, go back, take one single thread. Throughout all of human history, to my knowledge, certainly all of like known history, there has been a frontier to explore. Perhaps, if anything, like the last 30, 40 years has been like an anomaly where it's like the frontier was the internet. Now, obviously it's extended to space, but like some people will be totally fine in relational context. Some people will be totally fine doing, making good pants, making music, whatever.

1:22:47Like I make a podcast, but there is a sense that there is some deep human thing that it's hard for me to imagine going away, at least as a species of our desire to like have quests and grand adventures. and to be of consequence. And perhaps that last bit is the part that like was made up all along or we were deceiving ourselves all along. And maybe this is, this kind of goes hand in hand with a broader question of like, on some time horizon, do we get superseded in the local context of what intelligence means over here?

1:23:21Zhengdong Wang:Maybe, correct me if I'm wrong, but I would say like an assumption that your question is, is like there's this space of like questing that your quest could like do this, that, there's like all this unknown. And because of AI, AI is just like taking up a lot of this like space of questing. It's like 90 % of all the questing could be done that could be - Or theoretically 100 % of the globally relevant questing. Yeah. Maybe we'll still have locally relevant questing. Right, yeah. Or maybe we never had globally relevant. Yeah, so I guess like, yeah, maybe could could you talk about this assumption a bit because my assumption would be um it the the idea of like a hundred percent of the globally relevant uh questing uh would it would itself need like uh some justification or it's like your burden of proof to show because um as as long as like everything isn't like instantly uh completed instantly at like um you know zero cost or something like like let's say your quest is like oh i want to go to that galaxy over there and i want to explore everything and i'm taking all all these robots and like starships with me um and uh uh like when when you when you play a video game like everything is is done for you right you you still you still make these like vague decisions and and your your your choice of like this is who i want to be this is my identity is like still your choice there's there's still like choices that literally only you can make that.

1:24:52Zhengdong Wang:Is that true for like science? Maybe a pretty different way. Well, a few thoughts. Number one, the quote I read, which is like, your cleverness. What do you say? Later, you'll think who could possibly compete how your cleverness could be worth anything more than a hill of beans against an artifact that costs millions and thousands and thousands and thousands. You give a different example of the idea. we talked about it, AlphaFold or AlphaGo being, is it actually creative? Well, it doesn't really matter. A third thing I would say is like, you are someone, I feel quite confident, who could just go enjoy themselves all the time, write and eat food and visit art.

1:25:31And you do a lot of that, fortunately. And yet you're also like, no, I have to work on this. And maybe part of it is like, there's only a few more years, but we want to matter. We want to matter.

1:25:42Zhengdong Wang:Right. Maybe it is true that there is some kind of like, objective definition of what morality is or like just like objective answer to everything or like when you discover like true nature of reality there's this like theory of everything there's one equation or something like that maybe that is the case and maybe to take what you're saying like really really seriously I think that if we were to find such a thing and we were to all very deeply be convinced by that um that would be uh uh that that would be concerning or or or that that would that would open us up to exactly the kind of um um worry that that you bring of like everything is determined um there is nothing else that's really mattered we've like we've like done a hundred percent of the things that really mattered um you could think of it like that um You could also think of it as like, this is the completion of the game.

1:26:41Zhengdong Wang:Like the Minecraft, you've killed the Ender Dragon, credits start scrolling, and there's this nice poem written there. And that would be like the completion of the game of the universe. And in Demis' biography with Sebastian Maliby, he's like, once I know that, then I will shuffle off my mortal coil. Or he says something like that. Maybe that's one way to salvage it. But I agree that in that situation though, that would open this up to your concerns. But I think we are just so, so far away from that. And that even if our lifespans end up being much, much longer, I think a lot of it will just look like, okay, I've decided to take my starships and go to that galaxy and I'm gonna make a bunch of choices along the way that are like really, I find quite meaningful.

1:27:31I think that's right. I think that's right. I think on some level, there is a fear and a plausible reality that we stop being the most significant actors in the discovery of knowledge and the exploration of the universe and so on.

1:27:46Zhengdong Wang:I think this is all just relative to what previously culture or what we grew up in and maybe find it hard to change about our own preferences. Like if we grew up, you know, finding a lot of meaning in like fixing up our house or like tending to, you know, our livestock or something like that, then I think, I mean, every single generation thinks like, ah, this is like the kids these days, like everything's getting worse and changing. and now another way in which it's not different this time because it's always been different is that these kinds of changes are just happening faster and faster where like yes, the short term can be a lifetime but also it was great when the short term was longer than a lifetime or longer than the characteristic length of a career but now if you need to transition in like a space that's like shorter than the average human career then that's like a step change in new problems.

1:28:45Zhengdong Wang:If you only had to do it once because it's in the middle of your career, fine. And so in that way, it's different. Maybe now you're like, okay, this uncertainty is really worrying. I'm gonna have to change my life to adapt to this uncertainty. And then three years pass and you're like, I did it. I found new sources of meaning, found new things that I find matter just as much as what I previously did, then bam, I can do that now and you have to do it again. Yeah, so maybe another just like general personal thing of like being a lot more okay with change in like a meta way. A quote from you. In my time as a research engineer so far, I have enjoyed many, too many to count, meditations on research taste.

1:29:35My only contribution to the literature is this. Are you having fun? My question to you is, are you having fun?

1:29:40Zhengdong Wang:I am having a blast. Are you? I am. I am. I think part of this future we're talking about is like how, how much fun do you have or can you have by surfing the waves of change? And there are times where I feel afraid and there are times where I feel confused or like if you ever respond to that with a desire for inaction, I think you can spiral in the negative way in some weird sense it relates a little bit to like the classic Dan Nabeel like do more and you'll get more energy thing and so I think there are ways to respond to this all of this and be paralyzed and there are ways to respond to be like as you said there's so many galaxies to explore the galaxies I think are still quite far but the having fun is like there's always this type 2 fun of like you know people say you go on a hiking trip or there's like some experience you have a lot of uncertainty and then you look back and um um there's some nostalgia or like uh uh you were glad to have gone through the experience of course the experience has to has to go well right like of of course you can't ignore the um well uh if if you're hugely uncertain in the future because a lot of the things that you relied on um that your life depends on is like now um in in flight that's that is really bad um but that i think it is a it is a privilege to live through interesting times are you having type 2 fun or type 1 fun um i've recently asked this yeah um i think uh it is a lot of uh type 2 fun with very short feedback we're like you reach you reach the the end where you like look lots yeah you're climbing lots of hills yeah like like wow um like like even even now I think to a few years ago when chatGPT came out and I thought you know imagine the first time I tried chatGPT and before that the first time I tried language language some kind of language model that was not chatGPT or like imagining before that trying like image models like DALI just like how different everything was then it's like wow did I did I really you know live live through this and see it happen and like talk to people at the time it was happening that all feels so far away even though it wasn't that close.

1:32:03What do you mean by and why do you identify as a consumer?

1:32:08Zhengdong Wang:Yeah, so I was thinking of this when you were asking me if I'm having fun. And by consumer, I on one hand mean like the character you read about in your economics textbook. You know, there's producers and there's consumers. I'm just like, I'm the consumer. I'm just like consuming this stuff. And then a broader definition of like, I really mean like everything, like not just, you know, a nice restaurant, like a good movie, but also like rarer forms of consumption. Like I feel extremely privileged to, you know, know some of the, you know, much better AI researchers than me, like big characters in the fields, you know, the people who will map onto Oppenheimer and Rutherford and all these.

1:32:57Aliens in the future galaxy will be reading about.

1:32:59Zhengdong Wang:Yeah, yeah. Or later you read history textbooks and these people who are characters and to know how they feel about certain things, to be able to get their thoughts on something. That's just an extremely, extremely rare form of consumption that I feel very, very privileged to be able to partake in. Is research a type of consumption? No, I think it's production. You can get satisfaction and fun in discovering a fact and keeping it to yourself, and that can be a form of consumption. But producing is like, you've discovered this fact, and it's very cheap to share it, so you should share it. But one thing Tyler Cowen has said before, I think it was him and I've like just stolen it.

1:33:53Zhengdong Wang:I don't know if he still holds himself to this, but he's like, you know, I just produce so that they let me consume. And we're both selfish in this particular way. I was going to say, so at least you're producing a little bit. Most people's problem is that they would lean over too much into consumption. Perhaps in your milieu and certainly in San Francisco, it's the inverse. people only work. But yeah, how do you stretch balance? Yeah, yeah, yeah. There is not a perfect balance because I definitely have this like Protestant work ethic sort of thing or like I need to deserve being alive every day and that I should probably just like be producing 100 % of the time just to deserve being alive and deserve being as lucky as I am.

1:34:37Zhengdong Wang:Part of that is selfish in the way of like, you know, they won't let me talk to these really cool AI researchers if I don't produce anything, right? Like, I'm just not going to be... Sun consumption is unlocked. Yeah, yeah, yeah. It's like you've interviewed President Bush's personal assistant, right? Like, that's like extremely rarefied consumption or I so look up to that or like must be so cool. You get to try out, you know, on Air Force One, like what kind of special meal they have that day or something. you got the little napkin with the presidential seal on it but they don't let anybody do that you've got to be producing something either like writing as a White House correspondent or like guarding the president or be the president that's how you get to consume that I guess that's kind of what I do here I'm producing just a little bit so I get to be in the room yeah and it's super fun and maybe this is how the market works or is like, you want to consume this thing?

1:35:44Zhengdong Wang:Well, then you have to produce the thing that's like, this is the price of consuming this, is like producing this thing. I also think one should not be totally selfish, right? And production is good. Otherwise, we would not have all of the wonderful things. Well, soon the automated laser beams are going to be doing it all for us. And for most of the time, people wrote all that code by hand. Like, that was a lot of production. And I bet even if they enjoyed it, they might have been writing like slightly different code that wasn't all, you know, for one goal and purpose of being able to, yeah, of being able to consume better.

1:36:30What do you say to probably people who are more likely to be your peers who are, like, feel that there's no way they could possibly take time off or take a vacation in these pressing

1:36:44Zhengdong Wang:times ah well maybe to take the outside of that question yeah uh a bunch of things so um because we're on an exponential now is better than ever now is in fact the last time to um second all of the normal reasons why it's good like you know humans still operate on a certain time scale and if we are um you know packed end to end every day we really aren't doing any thinking and we're probably just like inundated by all the noise and information and and it will literally be worse for you the whole thing i could say about like mental health and that that being like the most important thing and so um if if you're thinking about this you should just probably take a break and uh it's it's just like win win uh across the board for everything um um practically uh you could uh vacation for a year and come back and your 20 a month subscription to ai will um just be like 10 times more effective.

1:37:36But what about the people who are working at these places? I mean, I've definitely talked to a number of friends in AI who are like, I literally can't imagine taking a day off.

1:37:46Zhengdong Wang:If you're having fun, that's great. I'm just saying, like, I don't think the cost would really be that much. And yes, I'm sure everybody is, like, contributing their own subjectivity and, like, the whole project is very slightly different. But you don't matter that much? But you do in the way that like, if you take a break, you know, the economy without AI will still grow at 2%, right? And both are true. You do matter and you don't matter. I think that's right. A quote from you. I think it's possible it's 2025 letter in one of the more recent essays. Jonathan Malazic in May reminded us that AI cannot teach us how we want to live.

1:38:31He writes of the humanities, I will sacrifice some length of my days to add depth to another person's experience of the rest of theirs. Many did this for me. The work is slow. Its results often go unseen for years, but it is no gimmick. I think we've hit this point probably plenty, but do you have any advice for people on how to live?

1:38:50Zhengdong Wang:Yeah, I think that's a beautiful quote by him and I quoted it at length and it's a great piece. When he wrote that post, he maybe laments AI a lot more than I do. And so I wanted to include it as like maybe to contrast some of the more optimistic about AI stuff. But when I read that, I think of it as like that is sort of the choice of making something matter in like the thought experiment you gave me earlier. Where, you know, there's this writing thing. Maybe you are doing it so that you could write things that other people would enjoy reading. And now there's this machine that can write things that other people enjoy reading more than what you were doing.

1:39:35Zhengdong Wang:And so that would feel like a loss of something that matters to you. At the same time, you and all your audience and everyone who's in this project writing and reading things together can decide, like, okay, but it's only going to matter if we wrote it, right? And we're going to make this choice. And it matters because it's hard. Like, uh, it's not, it's not easy for me to write this thing and it's easy. It would be super easy for me and other people would know it would be easy for me if I just like prompted the machine and then like I output the machine thing. So, um, the, the value comes from the fact that I spent, uh, a part of my short and precious life to write this thing for you, even if by some eval, it's worse.

1:40:19Zhengdong Wang:Um, and then, and then you've, you've like created, you've created meaning you've, uh, created, um, like real work that, that matters. as well. And I don't think it matters any less just because all the humans involved are like eating food grown by robots or something like that, because they've all decided, you know, that that that's fine. Like, that's not what we care about. So we get to make our meaning. We get to choose. Yeah. And maybe, maybe later on and like, I like a different level of distraction farther in the future. It's like, damn, I'm gonna, you know, send my starships out to these galaxies and the work is hard and um like to click click click this button or something like that like you're playing starcraft yeah yeah yeah um just a handful of additional miscellanea one of my favorite parts of that that recent letter is you talking about pluralism marginalia and optimism i think it's worth people go reading but one of the parts that that really anchors it so well is andor and season two of andor i love andor but i'll open up to you Why are those three values so kind of highly prized to you?

1:41:27Zhengdong Wang:Yeah, I think maybe pluralism is just like the most highly prized value to me, even though I recognize the contradiction of like, oh, what do you mean the most highly prized value is pluralism or something like that? And the other two I just wrote as sort of like themes to personal life of the year, where I got to travel to a lot of different countries, and I got to see a lot of like tiny bits of bureaucracy. And then I got to see a lot of people being so optimistic. And then for that letter, I wrote about Isaiah Berlin a lot. And I really imagine him as like both intellectually like a role model where I think I agree with him a lot about a lot of what he says about pluralism, not being able to like rank order your values as a lot of philosophies related to ai are very prone to to doing um the hedgehog and the fox as as you know um but but also like a sort of role model as like a consumer producer so where uh he in his life he um he basically like knew everybody who was alive at the time or you know got to talk to them and it's like um lived to this very full.

1:42:42Zhengdong Wang:He was a good hang. Yeah, exactly. Exactly. And he also produced stuff and he also spoke to the general public, right? Or a lot of his lectures or his essays were very helpful to outside academia, just explaining ideology in the 20th century. And one of my aspirations will be to just do a tiny bit to help explain technology, which I think is the thing of the 21st century, but it probably has always been. But she is also like a role model in that way. So talking about Berlin a lot, pluralism being an important value and the other two are mainly just like things that I felt like tied together the other stuff that happened in the year.

1:43:29Marginalia came up even in our conversation. It's the list of names, the people on the edges. What idea of Berlin's or peace of Berlin's would you think would be most impactful for people to know about or familiarize themselves with? Would it be Hedgehog and the Fox or something else? Or maybe not a piece, but just an idea?

1:43:47Zhengdong Wang:Yeah, I think just the idea of the Hedgehog and the Fox I found really fun. And people have mentioned, there's just something about animals, you know, imagining the animals. I liked your little short story, by the way. Oh, thanks. Yeah, so I think even just the idea and reading a few pages of the essay. So it's quite a long essay, and most of it is about Tolstoy, actually. So I found it super interesting. Yeah, it is maybe a bit separate from just the idea where he wants to write an essay about Tolstoy, but he's like, okay, but how do I introduce this essay? Tolstoy doesn't fit in these two categories perfectly in the way that all these other people in history, like, let's just begin with this thought experiment.

1:44:33Zhengdong Wang:like this is what a hedgehog is this is what a fox is who's a hedgehog who's a fox a hedgehog knows one big thing and a fox knows many things so you can think of it as like a generalist or like someone who's obsessed with something and then if you take in some kind of like consilience value pluralism everyone should really be both at the same time always it's always both just to wonder optimistically briefly for a moment how might things be if all this really works how might things be really great what are you excited about okay so uh also to connect it to um things not really being different because they're different all the time i think that in the wealthy world we basically have already reached this right like um um people who are very wealthy in the world today probably a lot of uh a lot of the people listening to this um are uh like never never have to worry about um food or water or things like that um um have a lot of choice in what they can do with their time um have a lot of a lot of choice in uh uh how they decide their own identity and what they value right of course there are limitations and as humans maybe we focus too much on the limitations of like i have to i have to do this i really wish i didn't have to do that and i think that this will become available to a lot more people we we have to deal with inequality as an issue but just like making everybody wealthier uh works when you know making people wealthier is like basically free um and um but but not only that but but second that like uh people who were already able to do this will uh sort of um come face to face with the fact that you should you should be doing this earlier you should be doing this now you could have all excuses yeah you could have always been doing this um um the the thing about ai as a thing just like pandemic as a thing or like um you know all these like serious uh a kind of like near-term like thought experiments you could do about your own life as a thing will really make you come face to face with it.

1:46:49Zhengdong Wang:Maybe people already are and that's why some people turn to religion, something like that. And I think we will just like be engaging with this question a lot more. I also really am inspired by like Demis says like maybe we will really find like the true nature of reality in some way that's very convincing to us as well. you write annual letters, largely inspired, I think, by Dan Wong. Yes. There was a bit where you're quoting Dan, advocating for the letters. First, Dan says, I don't understand why more people aren't writing them. It's not just about sharing your thoughts and recommendations with the rest of the world.

1:47:31Having this vessel that you're motivated to fill encourages being more observant and analytical in daily life too. And then you say, he's right. This letter, the only deadline I give myself every year is an immensely powerful nudge to do more interesting things during the year if only subconsciously it's the best antidote to the temptation to time box research writing or enjoying life how has writing these letters changed you how has it improved your life yeah i think

1:47:57Zhengdong Wang:um uh really a lot of it is subconscious where you think um okay well uh uh life is long or short however much you say it, when you think of a whole year, and I don't know if people usually think in the future in like 12 years, five years, right? You wrote somewhere, by the way, about like a 12-year plan. Yeah, yeah, because it's like so divisible, you know? But yeah, in the same way that you can't really plan ahead and then therefore you should really plan ahead, right? Like, yeah, this is a tangent. But because the near future is so uncertain, then if you were to think like, who am I going to be 12 years ahead?

1:48:41Zhengdong Wang:You really focus on what doesn't change, right? Or like, you know, what do I really value? That sort of thing. And that's also very clarifying. But yeah, subconsciously, I think through the year, you just think like, oh, this will be good for the bit. Are you writing throughout the year? No, so I have a big Apple note that I just put bullets in. And this could be thoughts or this could be, I have to probably fit in this important event in AI at some point or just to not forget it. Or the model releases are so fast or so frequent. I'm like, did that model come out this year or last year? It's just one big Apple note.

1:49:22is there anyone you really wish would write an annual letter i think all my friends should

1:49:26Zhengdong Wang:should write one it's hard that's all you write these are like 12 000 words but you only have to do it once a year so so i i don't think i'm very productive as as a person there are people who are like uh churning out like 3 000 words a week right it's harder when it needs to be uh some kind of synthesis or you're um you're reflecting on something instead of uh maybe maybe just just journaling and there's no set boundaries of how far back you have to go or what you have to cover. But it's easier in that it is personal. And it just so happens that personal stuff is scarce and personal stuff the AI will never be able to automate.

1:50:04Zhengdong Wang:But writing about personal stuff is a lot easier than, I think, than like, okay, you have to reinvent philosophy and come up with the new theory. You do a little bit of both. How have you become a better writer over the course of these? You've done four of them now? Yeah. So every year I write these. I also keep a little list of like, okay, these are things I have to remember about writing the next time around. Some of them are just things that everyone knows, but are still really hard to do. Like just getting words on the page is kind of the most important thing. And you have to get through the bad words to get to the good words um i think uh uh in in the same way of of uh in the rest of my life i like rewrite lists all the time um just it's sort of like um you have a row of your ducks and you're like patting all the ducks um just like yes you're still there and um i've like i've like done the next sequential thing on the list um i think that often uh rewriting like end to end um is helpful so even if you're writing the exact same words you it is sort of like you're reading it as a reader would read it and uh but by by the time um you're uh at the end of writing like a longer piece and you've spent a lot of time with it you're like lost in the sauce uh so for my last letter um just the opening like few paragraphs of like um how to uh sort of like just with words try to ai pill somebody um i it's like doesn't work on me anymore right because i've like, I've like read it so many times, but maybe you can salvage that a little bit by you, you start from a blank page and you just like write sequentially exactly as the reader would read it.

1:51:44Zhengdong Wang:And then, um, in a very short, uh, context, you, you load it all into the memory of like, okay, so the, the reader knows this fact now, and now I've introduced this proper noun. And so, um, I'm like loading the reader's context as they would read it. Then I would get to a point of like, Oh, this doesn't make any sense because, um, I'm like lost in the sauce. And so I've mentioned this concept before even introducing it or something like that. Wow. That sounds exhausting, but probably good advice. Probably effective. It doesn't take that long, actually. I think, at least for me, main bottleneck of writing is just like, am I writing directionally correct?

1:52:20Zhengdong Wang:Right? So all the time that I spent retyping the exact same words, it's not the bottleneck. And it can also add some momentum. Yeah. Yeah, yeah. get the panels going why do you love the economist obituaries oh yeah so um one is uh there's only 50 a year uh two is they pick subjects that are not um you know just like famous people so like if the queen dies the queen gets an obituary but um a lot of them are are people most people will not have heard of so um um someone who was just a really important uh member of this community, like this tiny island off the coast of Scotland. And there's this guy who's like really important to that community, for example, or the last speaker of a language, or someone who started a school for disadvantaged children in like this particular part of London, but like something like that.

1:53:19Zhengdong Wang:So I just love learning about this or like acquiring this new information that I never would have known otherwise. So a lot of it is curation. I think the curation is is excellent um i think that uh the fact that they're written from the perspective of the uh of the person um um in a way that's uh more like it's not fictional but it's like um there's like like more flourishes that are associated with like uh trying to put you physically in the place like um maybe there wasn't an ocean breeze but like who does it hurt to to pretend there was a breeze on this important day in this person's life.

1:53:56Yeah.

1:53:57Zhengdong Wang:Yeah. And all Economist pieces are like quite concise. And so it's just wonderful. One or two that you would very specifically recommend come to mind? Yes. Okay. So Pasha Lee and Albert Woodfox, both from 2022. and then I also want to say from that year Thich Nhat Hanh I emailed and wrote the editor saying she should do an obituary for him and she replied like I'm on it so I don't know if I actually made a difference but correlation causation that's pretty cool 100 Years of Solitude why is it your favorite? it's just really beautiful and I think it's a book about everything so everything is in it and maybe even more than 100 % of everything is in it because you've got people just suddenly like floating off to heaven and you know gypsies visiting your village showing off new technologies that never existed I just so so I think there's a there's a way of doing magical realism or trying to write a book about everything that just doesn't work and this is maybe it doesn't answer your question but I just feel like everything fits together so well or nothing feels out of place or nothing feels, this is just an extraneous detail or something.

1:55:22Zhengdong Wang:Somehow everything just fits in super well. And generally, in books and films and things, I like ensemble casts or many generations. It's just so rich. Have you ever seen Magnolia? Yes, yes, I love that one as well. A book I love, When We Cease to Understand the World, this is you. I won't presume to tell you what you should think after reading this book, but surely everyone who reads this book will agree. Any scientist who reads this book and also thinks their work is worth a damn should think something. I don't have a question. I just wanted to read that. That was good. I assume you've read The Maniac as well.

1:56:05Zhengdong Wang:Yes. I still haven't, but I'm curious which book feels more resonant for the time? Is it still? So I think when we cease to understand the world is more evergreen. And then for me, the last third of The Maniac, which was about Deep Mind and AlphaGo, I think it goes over a lot of the same ground of the documentary. So watching the documentary is good. But in general, I just think the author Labutat, so he's apparently friends with Dumbass as Jasmine. Crazy. And I think he is also really good at keeping in mind the sort of weirdness or the grandness of the scale. He would also be someone I would look towards whenever I'm like, oh, you know, is all we have really this techno singularity where at the end of it we get flying cars?

1:57:02Zhengdong Wang:No, we can be much more ambitious than that. We can, you know, we can like face the whole scale of all we don't know in the universe. And then that's really maybe the most ambitious we could be. There's a quote from him, I think in the interview with Jasmine, that I'm sure I'm going to butcher, but it's something along the lines of, that's the thing about humans, we're far better at being than we are at knowing. Yeah, everyone should watch that interview with Jasmine. Really good. We're in London. You seem to have a lot of love for this place. You've called it the best pre-AGI city and the best post-AGI city.

1:57:45That's right. What do you love about it?

1:57:50Zhengdong Wang:Other than the long litany of just like practical things like parks, best airport, I will not be elaborating, you know, food, all of these things. I just think there is um uh it's like a like a great representation of uh pluralism the fact that there has been um uh you know 697 lord mayors of london or something like that they're like like that that's existed for a long time there must be something uh something about the city existing for for that long um having such a diversity of like anything that you want to do you would be able to find um uh uh find a scene for it. The fact that people are so reasonable and so funny.

1:58:41A good place to be a consumer. Yes, for sure. The best place. Do you think you'll ever make a game?

1:58:46Zhengdong Wang:Yeah, I think so. And it's getting easier every year. So, you know, in terms of should you take a break or something? Yeah, I think I've always wanted to make like a Chinese history inspired Game of Thrones kind of thing. Yeah. I think people should write a series like this too. I've tried Ken Liu's Dandelion Dynasty. Unfortunately, I couldn't get into it as much, but I think there's a lot of room for that. What about container ships? Why? Why are you so into them? Maybe you're not so into them. I am so into them. They're just so efficient. Yeah. We don't wish for world government or anything.

1:59:32Zhengdong Wang:But the fact that everybody has agreed on this kind of standardization, I think the benefits of how much it's improved our lives is just hard to comprehend. Just, you know, how like people, they ship like trash to a different country to be like sorted and then like shipped back or something. That's probably, that turns out to be the most efficient way to do it, maybe. Okay, so there are a few ways that top-down total control or at least total collective decision-making can be pretty good. I think just agreeing on some standards, which doesn't seem like it should be that high stakes, just could have a lot of benefits.

2:00:17I think I referenced earlier, you often cite this Nabeel Qureshi and Dan Wong kind of advice on productivity, which is just do more. I think you say you can have free lunch across the Pareto front. you also somewhere else forgive me because i don't i i don't have the date written down so it's possible this was two years ago um but this is in one of the letters you say the problem is more general than exercise though if i want to read play music practice chinese and pick up new hobbies and it isn't happening more by now what makes me think it has a better chance of happening later it's time to either change or quit i was optimistic last year about a big virtuous cycle where doing everything makes everything else easier i'm going to take the opposite view this year that I should be honest about the actual trade-offs I face.

2:01:00Either way, it sounds trite, but I'll figure it out one day. Obviously, I don't think these things are fully mutually exclusive, but I think one of the things we kind of gradually learn, and sometimes they hit you in the face, is that there isn't that much time. And you really do have to choose. I think the doing more thing is also true, but I was just curious how it's going.

2:01:21Zhengdong Wang:Yeah. I think the year after that, I sort of even said slightly the opposite where I'm going to do more. And so, yeah, I think like a lot of things, it's like when we started off talking about research, you take a position that is maybe slightly too much to the extreme and you learn something about it. And then you just develop a better taste or prioritization so that in the future, you are doing the balance better. Do you ever let your computers idle overnight? So I think it just depends on compute allocation for the team where it's shared across the team. So I rest assured that the computers are never idle.

2:02:13Well, I feel like including many non-AI researchers, most of the people I know are paranoid and freaked out to ever leave Cloud not running on their computer.

2:02:22Zhengdong Wang:Yeah, but that's also no way to live. I think there are bigger costs to that, where yes, you're letting your computer or cloud idle. But if your production function, which I really think all humans are, you just need time to think and one should not be concerning themselves with tiny things like optimizing their usage so that you can focus on bigger problems. maybe you should hire somebody to use your quota efficiently but that you just need to be focused on the big problems and so there will be bigger costs that come with if you micromanage your quota your time. Maybe leave the optimization to the machines.

2:03:12Sounds good.

2:03:16Worth shouting her out because I'm having dinner with her tonight but I know you love it why do you resonate so much with everything's a scam?

2:03:25Zhengdong Wang:Yeah, I think it's just a great reminder. Like maybe in the same kind of thing or like every time you read a work of fiction, say Foundation, and it just like makes one point super, super well. Just like this is a great reminder. A lot of the things Riva Tez does is a great reminder. The fact that she made this a song and it's on Spotify. It's very much you can just do things. Everything is a scam. It opens up your ability to do things. I'm also very inspired by her opening a toy store in London. A lot of other schemes that she's running. Scam isn't so bad. It's just the rules are changeable or the rules are made up or not totally set in stone.

2:04:20Indeed. My last thing is a quote from Burke that you quote in one of your letters. It's felt to me fitting because it seems like a case for the long journey of research and discovery and adventure. I'm quoting now. By a slow but well-sustained progress, the effect of each step is watched. The good or ill success, the first, gives light to us in the second. And so from light to light, we are conducted with safety through the whole series we compensate we reconcile we balance we are enabled to unite in a consistent whole the various anomalies and contending principles that are found in the minds and affairs of men from hence arises not an excellence in simplicity but one far superior an excellence in composition i think it just encapsulates the uh point i was

2:05:10Zhengdong Wang:trying to make there but also what we talked about of like uh trying to make the um transition to powerful ai go well uh there is just a lot of talk about this time is different about step changes about um distinction right and that's very useful in um like shaking people right and uh getting them to feel the wave crashing over them. But once you get there, or sort of be careful what you wish for, maybe you don't want the prize on offer. And really the more effective or like the better way to do it is there are these promises that we've made before and we're going to keep them. And the important stuff is not going to change.

2:06:02Zhengdong Wang:The important stuff has always been there. AI just makes you face the questions that you should have been facing all along a lot sooner or at the right time. And it's great that something that Burke wrote so long ago is still relevant and a great point for him as well. Indeed. Anything else you want to talk about? That's all I got. Zengong, thank you so much. This was wonderful. Thank you. It's been wonderful. Thank you for listening to my conversation with Zhang Dong. You can share the episode with a friend if you want to help out. That certainly means the most. You can also rate it, give it a review on Spotify or wherever you're watching or listening.

2:06:45And of course, subscribe or follow too if you want more episodes. And once again, I'd like to thank Notion for making the show possible. Like I talked about with Zhang Dong, the capabilities and the speed of improvement in AI is very hard to keep track of. And the way Notion integrates AI and agents makes it easy to have a single place where you can actually coordinate everything and have access to the latest models the day they come out, whether that be OpenAI, Anthropic, Google, open source models, or otherwise. I think the way the future of work is going is that you and your collaborators will manage and work with a wide range of agents doing all kinds of different work and use AI to give you leverage on the work that you don't want to automate.

2:07:27Notion is the ideal hub or even operating system to run your company, your team, your project from because you have access to the work itself, all of your collaborators, and these agents that give everyone superpowers. Thanks again to Notion, and you can learn more at notion.com slash dialectic. Thank you for listening and supporting the show, and I will see you next time.