The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 30 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 2 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Patel: Individuals will eventually train superintelligences in basements
“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.”
Patel: Reinforcement learning may not generalize beyond verifiable domains
“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.”
Patel: Online continual learning is not imminent for current AI architectures
“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.”
Patel: Pre-training scaling is seeing diminishing returns
“Pre-training, which is this idea that you just make the model bigger that has had diminishing returns.”
Patel: 50% chance of real AGI by 2032
“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.”
Patel: AI labs will keep spending exponentially despite diminishing returns
“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 …”
Patel: 4x annual compute scaling cannot continue beyond 2028
“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…”
Dwarkesh Patel: Roughly 30% chance of an AI intelligence explosion
“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.”
Patel: Continual-learning AI could replace white-collar jobs worth tens of trillions
“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.”
Patel: Misaligned intelligences will emerge, requiring societal resilience
“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.”
The public will see a GPT-5 level AI model by year-end
“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.”
Frontier AI scaling will hit a 'data wall' before GPT-5
“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…”
GPT-5 will enable autonomous agents to execute UI tasks for hours
“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 only tech giant with successful custom AI chips
“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.”
Compute will be less of an AI bottleneck than energy availability
“I think compute will be less of a bottleneck than energy.”
Training next-generation frontier AI models will soon require gigawatts of power
“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.”
AI models capable of automating AI research are plausible within five to ten years
“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.”
Patel: Reinforcement learning 10x compute scaling can only continue for a year
“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…”
Patel: GPT-4-Level Training Costs Have Dropped 10x to 100x
“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…”
Patel: AI deception could worsen as training tasks become less understandable
“The problem might get worse over time as We're trading these models on tasks we understand less and less well.”
Patel: China Adds a US-Sized Power Grid Every Few Years
“And what's more important is that they're adding an America sized amount of power every couple of years. It might be more longer than every couple of years. Whereas our power production has stayed flat for the last many decades.”
Microsoft loses leverage over OpenAI if the board ever declares AGI
“The clause in the open AI charger says that if the board, which is nonprofit and controls the company decides that we've built AGI, then Microsoft has no leverage over, over open AI anymore.”
Nation-states will eventually become the primary funders of frontier AI scaling
“So I think in the world where AI continues to get much better at a fast pace, I think you're looking at a much more involved. I guess I'm trying to say the players will be nation state level players, because that's also the kind of funding you'll need to keep …”
China developing AGI first would grant massive military leverage over the US
“In the world where they happen within a few years, I think what you're looking at is China has a ton of leverage over the United States because they, one of the things future AI could unlock is things like pocket nukes, right? And so China is ahead. They could…”
The median future outcome of artificial intelligence will likely be positive
“And I mean, I'm still expecting a great future because of AI. My expectation is like the median outcome is good. I think we should worry about the cases where things go really off the rails and do what we can to reduce the odds of that.”
Patel: RL scaling is outpacing pre-training scaling
“RL scaling is happening much faster than even overall training scaling.”
Dwarkesh: Hyperscaler ASICs will come online from all major providers
“And so that just sets up a huge incentive for all these hyperscalers to build their own ASICs, their own accelerators that replace the Nvidia ones. Which I think will come online over the next few years from all of them.”
GPT-5 will have noticeably improved reasoning capabilities from step-by-step training
“I think it'll definitely be better at reasoning, which is trivial to say, because the training methods that we've seen them talk about, like you, I'm sure you heard the talk about Q star and what it seems to be is training the model to rewarding it on getting …”
AI will improve at AI research faster than at other commercial tasks
“The people making these models are AI researchers themselves, and I can imagine them being selectively trying to clearly they hear about their use case, which is helping them with their job, so I can imagine the model getting better at that than it gets better…”