How AI Could Concentrate the World’s Labor in a Few Companies - Dylan Patel

transcript

One thing I find crazy about these scenarios is just how much of the world's future labor supply ends up in very few companies and also how fast the labor supply grows year over year. So if like computer the frontier you know in flop terms is growing four or five x a year. And further the computer required to achieve the capabilities like decreasing three x a year. So the computer the frontier the basically effective AI population size at the frontier lab is increasing 10 x year over year. And so that doesn't really matter that much right now because AIs are not good enough to do full jobs or be like as autonomous as people in their capacity to do work or pull off schemes or whatever. But if the current trend continues you have a world where OpenAI goes from having say 10 million basically AI laborers this year to 100 million the next year to a billion the year after that. And then pretty soon even if compute scaling slows down it doesn't take up many more years before each company individually has more labor equivalents than there are people on Earth. Um and I think that's like a thing that is very plausible by the end of this decade that there's more AI labor more effective population within a single lab um than there are people on Earth. So we talk often about centralization of power because of nationalization or whatever but we don't think enough about the fact that we're actually moving very fast into a regime where most AI labor or sorry most most people like in terms of like the work output or something is just like concentrated within two labs who are consuming more and more of the world's compute and so if if these AIs are misaligned then most of the world is misaligned basically because like most of the world's minds are there um but even if they're not it's just very few companies have like a lot of influence or a lot of control

It's of there's the whole spat recently where it's like I think Gavin Baker was like and Dario believes that there's only going to be one company in the world and then you know Sholto and Dario came out and were like no no no we didn't say that. But ultimately you know if you believe in RSI you believe in the labs are the most effective user of compute and can generate the most value from the compute then the only thing that's going to happen is centralization of compute and if you believe in you know sort of AI researchers RSI AGI then all of this exists all of this is the base.

This is even true if there's no RSI. The current effective like effective population of the frontiers is currently increasing 10x year over year for a given level of capabilities right? So if you get to the level of capabilities which is a human a very competent remote worker or like a very competent software engineer or very competent researcher. That population of those would like 10x year over year at the current rate of current rate of capabilities

without RSI and then once you have RSI it's going to be crazy.

maybe it'll be growing like 100x year or 1000x year or like intelligence is increasing but the population isn't increasing or some mixture of the two right?

Yeah I mean I guess I guess like what world do you see Dwar Kesh where everything is not centralized because it seems to me that every force is screeching towards centralization and that's scary as hell.

Yeah.

I don't I don't you know I would love for it not to be centralized completely but maybe that's that's the whole point of the a machine that loves grace right? Is is it is everything and it makes our lives great.

Yeah it's so hard to think about the future but I agree with you that I think the fundamental problem is that lab AI training has huge economies of scale because any effort you spend into training an AI for a specific skill or specific set of knowledge gets amortized across billions of sessions or billions of users. Furthermore so that's like one effect the other effect is if you're slightly ahead in the AI race and computers in shortage, you can charge a much higher mark off because you can better economize the scarce resource. So, there's the two effects which are given more and more to the person who's like ahead in the AI race. There may be more, right? So, if there's a models are learning from deployment and one model is like deployed much more widely than another one. It's getting much more like real-world data.

Yeah, your point your point is taken that like whether it's user deployment and continual learning, um whether it's uh training having these economies of scales, um whether it's incremental progress that the the best AI model helps you to make the next AI model,

um RSI, all of these things Oh, sorry, I didn't even mention RSI.

All of these things point to centralization.

So, I think one of the big intellectual projects, honestly, um that yeah, we should spend some time thinking about uh async or at least I will spend some time thinking about is what is the vision of like a decentralized broadly empowered future after AGI that takes these economies of scale seriously? The other one of vision is that the government controls it. And maybe you think you can trust the government more because it's not private corporation.

I don't trust the government and I don't trust Dario and I don't trust Sam.

Yeah, yeah. And [laughter] that's a problem, right? Um but there's no at least Obviously, obviously it's like very easy to be wrong about the future and you don't anticipate a key effect or something that changes everything. But ex ante, it's very hard to see a reason why there or like how we avoid a scenario where we have to choose one person

like capitalism worked, right? It's the decentralized decision making and decentralized power. And why super centralized capitalistic economies actually grew slower than super decentralized capitalist economies to some extent. You have to have rule of law and all this. But then AI flips all this on its head.

Right.

And ultimately, you're like actually private ownership is probably not the most efficient economy and therefore it grows slower than an AI economy which is centralized.

ownership, but it's like how many firms are really involved in this This is like the share of the economy that's like what, like 5% of the economy or something like that in the US. Sorry, 1 trillion divided by 30. It's less than that, sorry. But, yeah, maybe two 2% of the economy right now. It's like Nvidia is a huge share of it and then Anthropic and OpenAI and these hyperscalers. And obviously there's other firms involved, but like a large share of the AI stuff is just happening from very few companies. So, it's like it could be private property, but like very few companies are involved.

I mean, this is what the structure of the market is doing, so

Yeah, yeah, yeah.

what what can prevent it? I don't know. I don't unless AI progress slows down, unless governments regulate the [ __ ] out of it. This is all that happens, in which case you know, we're heading for a world where either we have super concentration of resources and we pray that that one company gets everything right, or we have government slow everything down and people slow everything down and and you have a slow down of progress somehow, hopefully. And and there is a more of a balance of power and even as we go towards an AGI, ASI, RSI, um everything along the way will still lead to someone's going to allocate going to capture more resources. So, so it's kind of hard for a framework in which AI doesn't lead to super concentration.

Yeah.

Now, the one positive thing here is that today Anthropic does not capture most of the value. So, we can talk all we want about, oh, you know, they went from $20 per megawatt to $100 a megawatt, but they're still paying 13 um for a lot of the compute they're buying. But, at the end of the day, the reason they've gone to $100 per megawatt is because Jane Street is capturing $300 per megawatt or $500 per megawatt. Um or Dwarkesh from researching his podcast and learning about credit is capturing, you know, how many dollars per megawatt? Now, how much can you use?

[laughter]

Tough.

Yeah, yeah, yeah.

Um but, you know, I think I think that's the like one saving grace is that the rest of the economy maybe profits so much more from Anthropic

the whole logic I was laying out earlier of them reallocating inference to AI R&D, the whole logic of that is that the returns to labor inside AI AI labs is much higher than the returns returns outside, yeah.

This is my cope. I agree. In in all scenarios of the world, you know, there's 80,000 worlds and only one of them Anthropic doesn't own the whole world. Is Is that [clears throat] Is that you know, again, power concentrates because I don't want to send the tokens outside. They're more valuable inside. And so it's the same thing, right? Why would I let Jane Street, you know, make all this money off of these degenerate options traders?

Hey, there's some

There's a sponsor. Come on.

[laughter]

Jesus Christ.

No, I think it's great. I think it's great. It's a good value for the world to make it an efficient market.

Yeah, yeah, yeah.

[laughter]

You know, Jane Street making all this money off of getting the world view correctly, making money off of degenerate options traders, whatever it is, you know, why would Anthropic allocate compute to that? If If If If the end, you know, monetization that Jane Street has per megawatt is 200, so they're willing to pay Anthropic 100, well, what if Anthropic can just generate hundreds of millions of dollars per megawatt by using that compute internally? And that's that's what's happening.

Yeah, yeah. Well, on that somber note, I guess I guess uh I guess we'll meet again when the RSI is officially kicked off.

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