Anthropic Genius Predicts the Next Decade

0:00 We're concerned because we're going to get something that's a drop in for a human, right? It's going to be as good as a human at everything they can do on a computer. It's going to be once we have robots as good as a human at everything in the physical world. But at the same time, that unlocks massive like radical improvements. It means you can literally take technology that would have required the next couple of centuries to develop with our population and compress that into the next decade, couple decades. I'm already seeing this with like aerospace where there's airplane design stuff that's going so much faster that there's probably really advanced planes we would have gotten in like the 2040s that we're probably going to start seeing I think in the next few years is really cool.

0:32 >> So you can keep increasing and potentially doubling the productive intellectual and physical capacity of humanity in such a way that allows you to truly get to a post scarcity world like this is a world where literally everything is reduced to the cost of energy where building homes is reduced to the cost of energy. >> Yeah. The the middle class will all have giant homes if they want. >> Giant home. You could you could literally have whatever you want in that wall.

0:54 >> Yeah. You can go to the mountain and do like a 500,000t thing and it's a middle class thing. >> Exactly. Exactly. That would be middle class thing. In the same way that things we have today are unimaginable to even the kings of like centuries ago, right? where we've cured every disease where people actually probably we've cured longevity. and so you're in this world where literally the the abundance everyone on earth has a level of abundance available only like not even to the richest people in the world today. and that's the world we're fighting for. But it's a very tricky world because it means that you need to like one you have to sort of chart this course through to it and two you have to figure out well how do we even like share the proceeds of that world in such a way that you don't end up with massive inequality right that the returns don't just flow to people who h happen to have capital in the pre-existing world and instead everyone if they so want to can have that kind of abundance and so there's a big social political question of of like how do you share in the in the benefits? Yeah, there's a lot of mistakes you can make by assuming we're already there though too, right? Because the dignity of work right now is really and we're not there. We're not even close to there, right?

2:00 >> but if we invest in the technology in the right ways, then then we've got a shot of getting there. And so we think that like basically let's let's like draw the trend lines out a little bit from today, right? over the course of the last four or five years, we've been 2xing or 3xing the amount of compute capacity devoted to AI every year. and an interesting question will be and so I think that's roughly together the hyperscalers are spending about a trillion dollars this year on on capex related to to AI. A very interesting question will be will that keep that trend line hold right and so will it go to $2 trillion next year and then $4 trillion in 2028 and if that trend line broadly holds and you can sort of maybe expand that to encompass the broader robotics industry and this kind of stuff then that means that in the early 2030s or something like this you start to get to the point where you're actually effectively doubling the like the GDP of humanity in the early 2030s which again a little bit of a ridiculous concept requires a lot of things to go right >> but >> it see it seems like the productivity growth could just start >> productivity go really I mean yeah and it feels like it should even be in the next couple years I think something we really notice like in the statistics Kevin Walsh is the new chairman of the Fed he is I don't know if he's AGI pill but he's very bullish on AI productivity right now very smart friend of ours like it feels like we're going to start seeing that a lot more but then that' be like the kind of it feels like insane to say but it could just accelerate much >> it just could accelerate even more and I think Like one of the interesting charts I saw recently was this chart of of employment actually in the Philippines which went up.

3:39 >> I was surprised by this. I thought the BO was going to get really hit there. BO stand for business proc outsourcing. They're doing like the low-end call centers but and yet they're still growing. >> And yet they're still growing. And actually software engineering employment is up as well. >> and I think a lot of this is because all of a sudden people are dramatically more productive than they were before. and a very interesting trend line would just be like how long does this bump continue where people you're sort of you're pairing in in the same way like >> there's so much more to do. There's so much more to do. You're using this stuff with this positive sign.

4:07 >> I I well at least in the short term it seems that way. But I do think I do think it's important that we we we we don't convince oursel too much that it's just like all going to be fine for be disruptive volatility >> right now. Right now, as Shto put it, you're in this in this. actually possibly good moment where all your employees are still very important parts of taking advantage of AI. >> Yes.

4:32 >> And as a result, what happened is you got an enabling technology that made every one of them more valuable. And so you wanted to hire more of them. >> But at some point, our belief is that we're going to go from a world where you need a human paired with an AI model to sort of get all the value out of it to a world where you don't. And I think that's the world where we start to get very nervous about the consequences of >> this is like with chess for 30 years it was like the best chess player was a human plus the machine and now the machines are just crashing >> and we think that's just a much shorter what a time period.

5:02 >> Yeah. >> I think I think one thing that was a big update for me over the last three years was when I first started maybe over the last five years when I first started thinking about sort of the rate of AI progress. I I believed eventually we would sort of get to a place that looked like where we are today or where I think we'll be in a year, but that it would take longer. And in large part, I thought it would take longer because I thought that scaling the data required to do this was just going to be an extremely extremely time and dollar dollar expensive pursuit. and the thing that happened that even by my sort of like lofty expectations at the time of AI progress was was was unexpected was sort of that the the the ramp of the revenue and the scale of these businesses of anthropic and open AAI was so fast that all of a sudden it became completely plausible for the people developing this technology to throw money at the problem of blasting through much faster.

6:08 what we thought a lot of these bottlenecks might be. The compute ramp is another great example of this. It would have been inconceivable to most people 5 years ago. We would spend a trillion dollars in a year in conceivable to people a year ago, >> right? It was a year ago. >> And so it is kind of cool how it worked out how all these giant tech companies always had like hundreds of billions of cash they were hoarding and we kind of we criticize them for it and now they actually were able to use it now right at the right time. It really worked out.

6:36 It does seem like we are in a timeline where >> a lot of stuff that actually has is is sort of very large interaction term with each other is happening at once some good and some bad right we talk about the the the the the move into space for compute it's like kind of interesting that like AI is coming around at roughly the same time that SpaceX is coming into its own very well it like the timing of that was like really interesting you could imagine if if SpaceX had taken 10 years longer to get here that AI timelines might have might have existed.

7:09 >> It's only thanks to Elon too. He was like crazy enough to start it like way before anyone else. >> On the other hand, by the way, you have some much more concerning things that are happening. Like I don't think it's great for the world for all sorts of reasons, including race dynamics, including that AI I think fundamentally is a technology that can benefit authoritarianism more than more than most other forms of government. That AI is arriving at a time when we're entering one of the like certainly the most bipolar world in my lifetime. Isn't that linked though? Like isn't isn't isn't the isn't there something about like social media and like how it uses machine learning and how it uses improving AI that does polarize us like something about the attention >> I think when I'm saying bipolar I'm really referring to sort of like the China US global picture you don't mean the left right polarization US no I mean that's probably another thing that's worth thinking about but I I I I really do think I would have updated us at least slightly more positively on like the prospects for AI going very well if if it was coming into the world say in like the early 2000s when you have this very unipolar >> more unipolar world it's more safer >> it's like a tragedy worthy of a sci-fi novel that the most valuable resource in the universe is produced in this little island between the two world superpowers Whatever.