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 68 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.”
Dwarkesh: AGI requires further algorithmic progress, not just current model scaling
“I don't think we're just right around our corner from AGI and it's just a little additional dash of something. That's all it's going to take. I think, you know, people often ask if all AI progress stopped right now and all you could do is collect more data or …”
Dwarkesh: Lack of continual learning prevents LLMs from replacing human labor
“I think a big bottleneck these models have is their inability to learn on the job, to have continual learning. Their entire memory is extinguished at the end of a session. There's a bunch of reasons why I think this actually makes it really hard to get human-l…”
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…”
Patel: Multi-instance continual learning could create superintelligence without recursive coding
“Once continual learning is solved, you might have something that looks like a broadly deployed intelligence explosion, which is to say, That because if these models are broadly deployed to the economy, every copy that's like this copy is learning how to do plu…”
Patel: Delayed Reward Signals Will Slow AI Progress on Long-Horizon Tasks
“Now if we're getting to the world where you got to like do a project for seven hours and then at the end of those seven hours, then we tell you, Hey, did you did you get this right? Then like the progress just goes on a bunch. Cause you've gone from like getti…”
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: Meta treats Llama as a toy rather than approaching AGI correctly
“I think they're treating it as like a sort of like toy within the meta universe. And I don't think that's the correct way to think about AGI.”
Dwarkesh: AI adoption is bottlenecked by model capabilities, not token cost
“The reason they're not being more widely used is not because people cannot afford a couple bucks for a million tokens. The reason they're not being more widely used is just like, they fundamentally lack some capabilities. So I disagree with this focus on the c…”
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.”
Patel: Future Economies Will Be Denominated in Compute, Not Human Labor
“More importantly, I think the future economy, once we do have these AI workers will be denominated in compute, right? Cause if computer's labor, right now, if you just think about like GDP per capita, because the individual worker is such an important componen…”
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 …”
Tech giants should concentrate capital into a single frontier lab
“The thing with AI is if you buy scaling in this picture, that is, you make the models bigger, they get much smarter. Then I don't think it makes sense to hedge your bets in this way. I think you should just double down, give, give one of them a hundred billion…”
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.”
Generating synthetic data could impose a 5x compute tax on model training
“It will make training more expensive because instead of just doing one backward pass, you now potentially have to do many forward passes because at each forward pass, you're going to come up with some output. Then the model has to decide which of those outputs…”
AI scaling will not mysteriously halt halfway through the range of human intelligence
“It would just be bizarre to me that, like, you're halfway through the human range of intelligence, and now it stops getting better, so I do sympathize with Sam's statement in the sense of, like, why would it stop here, right? If it was gonna stop, why, it woul…”
We cannot be certain current AI development is actually tracking to AGI
“You shouldn't be, like, sure that they're gonna we're on the track of AGI because, yeah, fundamentally we don't know what kinds of things these are.”
If AI scaling stalls, it will likely be due to data memorization
“If, let's say, GPT-Six isn't that much better than GPT-Four, and you had to look back on it and say, like, why, why did that happen? I think the most, the thing I'd expect to say is that right now we are We are kind of fooled by how much data these models cons…”
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.”
Recursive AI self-improvement will require government intervention to pause development
“So I think in the world where you have really fast AI progress, and you are coming up to this point we're talking about where AIs can help improve themselves, then I think what you want to do is you might need a sort of government level actor to be like, all r…”
Dwarkesh: Slow enterprise AI adoption stems from model limits, not stodginess
“And so sometimes people say, well, the reason Fortune 500 isn't using LLMs all over the place is because they're too stodgy. They're not they're not like, they're not thinking creatively about how AI can be implemented. And actually, I don't think that's the c…”
Patel: Prompting alone cannot teach AI models complex capabilities
“I don't think prompting alone is that powerful a mechanism of teaching models, these capabilities.”
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: Training AI on math will not yield diplomatic acumen
“I just don't think you're going to train the AI so much on math that is going to learn how to do Henry Kissinger level diplomacy. I do think skills are somewhat more self-contained.”
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: One-month lead in intelligence explosion yields winner-take-all dominance
“Look, if there is an intelligence explosion, it has a really tough dynamic because if you're a month ahead, you will kick off this loop much faster than anybody else. And what that means is that you will you will be a month ahead to super intelligence, but nob…”
Patel: OpenAI's o3 is currently the smartest AI model on the market
“I do think O three is the smartest model on the market right now.”
Patel: xAI is slightly behind leading labs but has high compute per employee
“I think they're a serious competitor. I just don't know much about what they're going to do next. I think they're like slightly behind the other labs but they've got a lot of compute per employee.”
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: Effective Altruism's Reputation Remains in Tatters
“I do think the movement and the reputation of the movement is like still in tatters.”
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.”
Individual AI scientists are probably replaceable at large research labs
“Then I, you know, I think like the default perspective is listen, you've got thousands of scientists who are doing AI. Surely any one of them is replaceable. I think that's probably correct, but. I'm not in the field enough to know that.”
Claude 3 and Gemini are not significantly better than GPT-4
“So we've gotten Claude III, we've gotten Gemini. They're not significantly better, if at all, than GPT-IV, and certainly not the newer version of GPT-IV.”
Standard AI benchmarks like MMLU are becoming saturated and inadequate
“I mean, like, people will come out and say, here's what we got on MMLU and so on, but they're getting saturated, and they're not, often not that great to begin with, so I, I'm more eager to see what it feels like to talk to one of these things than learn what …”
Chatbot Arena fails to properly evaluate long-form conversational context
“And in fact, I think even chatbot arena has some deficiencies in terms of evaluation because from what I understand, you're doing these pairwise comparisons, but you're doing them you ask a question and two of them respond. And what I'm more curious about is w…”
Microsoft is repeating Google's mistake by splitting AI model training efforts
“Microsoft is basically reversing what Google has managed to do over the last few years. And in fact, making the same mistake that Google initially made, which was to have its training distributed or split up between two different corporations or institutions.”
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 …”