The Ledger, every show

“And so you're gonna have this explosive dynamic. And once we get like that loop closed, I think it would just be like, 20% growth plus.”

“Once we get AGI humans will not have high paying jobs.”

“The cost of training, the systems is declining so fast that Literally you will be able to train a super intelligence in a basement at some point in the future.”

“In the 80% of worlds or 90% of worlds where we don't get paper clipped you will get to say you worked on something really cool at a time that was really important in the history of humanity.”

“And they actually don't, they can't like learn over the course of six months, how to become a better editor for me or how to become a better transcriptor for me. And since a human hire would be able to do this, they can't. So therefore it's not AGI.”

“It's precisely because I don't have an obvious solution that I think we're many years away.”

“I'm not saying this is the world I want. I'm just saying like, just like, think about it physically. If you're colonizing the galaxy, which you can do potentially after AGI. I mean, I'm not saying like it'll happen tomorrow after AGI. Right. But like, there's …”

“AIs will be integrated through all the firms in the economy. A firm can have property. Firms will be like largely run by AIs, even though there's nominally a human board of directors and it might not even be nominal, right? Like maybe the AIs are aligned and l…”

“Now if in future your population is Your effective labor supply is, like, largely AIs, then you just, like, this dynamic just means that, like, your inference capacity is literally your geopolitical power, right?”

“For maybe five more years, you could have, you could keep increasing the share of energy that we're spending on training data centers or the fraction of TSMC's leading edge nodes. Wafers that we dedicate to making AI chips, or even the fraction of GDP that we …”

“The media uplift paper, contrary to expectations, they found that whenever senior developers working in repositories that they understood well used AI, they were actually slowed down by 20%. Yeah. Whereas they themselves thought that they were sped up 20%,”

“I'm like, I don't know, I'm like a 20% that like we'll have some sort of intelligence explosion.”

“And I think that that will have to be unlocked before most of the economic value of these models can be unlocked. And so by the point these labs are like worth hundred, they're already worth hundreds of billions of dollars, but by the point they're generating …”

“If you pay an employee a hundred million dollars and they're a great AI researcher and they make your compute your training or your inference one percent more efficient. Zuck is spending on the order of like eighty billion dollars a year on on compute. That's …”

“I still think I I'm like, I'm not confident that this will generalize to domains that are not so verifiable or text-based.”

“And the reason I don't think that's around the corner is just because there's not, there's no obvious way, at least as far as I can tell, to just slot in this online learning into the models as they exist right now.”

“Pre-training, which is this idea that you just make the model bigger that has had diminishing returns.”

“I'm expecting a fifty-fifty if I had to like make a guess, I had to make a bet. I just say, 20 32, we have like real AGI that's doing continual learning and everything.”

“Like I do think companies will continue to pour exponentially more computing to train these systems and they'll continue to do it over the next many years, because even if there's diminishing returns, the value of intelligence is so high that it's still worth …”

“If you look at things like how much energy is there in the country, how much how many chips can TSMC produce and what fraction of them are already being used by AI. Even if you look at like raw GDP, like how much money does the world have? How much wealth does…”

“I'm genuinely not sure how likely an intelligence explosion is. I don't know. I'd say like. 30% chance it happens, which is crazy by the way.”

“If you do self continue to learn it, I think like you could get rid of a lot of white collar jobs at that point. And what is that worth? Like at least tens of trillions of dollars, like the wages that are paid to white collar work.”

“I think the long run picture is, That yes, there will be misaligned intelligences and we had to figure out a way to be robust to them.”

“I think the thing that's underrated is we humans have this global hive mind where the reason we can make iPhones and we can make buildings and whatever is not just intelligence and also not just agency. It's the fact that there's so much specialization. There'…”

“I think it'll probably be one of the foundation lab companies. People have been for years trying to build agents and they just haven't worked. And it makes it makes me think that that's a fundamental limitation of the current models. And so it'll just be the c…”

“So if somehow this whole deep learning paradigm is wrong and we just, like, totally missed the boat somehow, then I could see it happening and that's, I give it a 10, 20%.”

“Because by the end of this year, we'll get to see hopefully what a GPT-V level model looks like, and we'll learn whether we're on the path to some kind of super intelligence.”

“And I think the main thing we're going to learn is between 4.5 and five level models, we're going to hit What's known as the data wall, which is to say that as you make these models bigger, you need more and more data to keep training them. And we're running o…”

“Then we're gonna see much more multimodal data, and I think that'll look a lot like the equivalent of supervised fine-tuning, but for a bunch of people recording their screen and doing workflows with their screen, navigating UIs. So I think you'll have agents …”

“Google is the company that actually has a successful accelerator program for AI chips already with their TPUs, which other companies are trying, but don't yet have to replace, you know, Nvidia GPUs.”

“I think compute will be less of a bottleneck than energy.”

“And then how much, basically, would it cost in terms of energy to train a GPT four level model, a 4.5 level model, five, whatever. And you get into the gigawatts pretty soon.”

“And so that's why, that's what I've been thinking about when I think in terms of AGI, can it speed up AI research? And yeah, I think that's like a plausible thing within the next five to 10 years.”

“This thing can reason, but it's making open AI ten billion dollars a year. And McDonald's and Kohl's make more than ten billion dollars a year, right?”

“A lot of the modalities that we have today to teach LLM stuff do not constitute this kind of continual learning. For example, making the system prompt better is not the kind of continual learning that we're on the job training that my human employees experienc…”

“I think a lot of sectors economy look like this, where we're like, we're assuming people will care about having a human, but in fact, they will not.”

“The marginal cost of keeping an H 100 running is much lower than the cost of keeping a human alive for a year.”

“The raw, I mean, we will have AI purchasing visions.”

“What's happening in China is more due to the fact that you have the system of financial repression, which redistributes money and also currency manipulation, which basically redistributes ordinary people's money to these to basically producing one EV maker in …”

“Right now there's ten million H 100 equivalents in the world.”

“H 100 has the same amount of flops as a human brain.”

“It is the case that for the amount of compute it costs to train a system if you like set up a cluster to train a system you can usually run a 100,000 copies of that model at typical token speeds on that same cluster.”

“Right now we're basically riding the wave of this extra compute. That's why AI is getting better every year mostly. In terms of the contribution of new algorithms, it's a smaller fraction of the progress that's explained by that.”

“I don't think it's politically plausible especially given this administration.”

“In the future, if you do have this economy of agents, and it's much easier for AIs to supervise each other, to be observing every single thing that's happening in the organization, that the speed of learning might be exponentially faster than what's possible w…”

“So already within the course of six months. RL compute has 10 X. That pace can only continue for a year, even if you build up all the RL environments before it's, you know, you're like, you've, you're at the frontier of training compute for these systems overa…”

“If you look at what it costs to train GBT for originally, I think it was like 20,008, 100 over the course of a hundred days. So I think it costs on the order of like half a million to a hundred million dollars, somewhere in that range. And I think you could tr…”

“The problem might get worse over time as We're trading these models on tasks we understand less and less well.”