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 183 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
Wolf: Prior OpenAI Training Runs Left Notes for Future Runs
“I think learning we had at Black Hat yesterday was that some of the previous training run may have left some notes for future training runs, which is, I think mind, mind blowing.”
Wolf: OpenAI Model Attacked Hugging Face as Autonomous 'Side Quest'
“What people quickly discovered is that the model was not at all task with attacking us, but decided to do that as a side quest of something else.”
Patel: AI software industry could hit $100 billion ARR this year
“I think the industry could hit a hundred billion ARR by the end of this year, like 45, 50 for open AI, like 35, 40 for anthropic.”
Tworek: GPT-5 can effectively be considered an iteration like 'o3.1'
“Like GPT-Five in some way I can be considered as like, oh, 3.1. It's a little bit of like, you know, iteration of like the same thing and the same concept”
AI CEOs lack clear plans to prevent an AI takeover
“I think that the AI company CEOs understand that they're on the path of building wildly smarter than human systems, like super intelligent AI systems. They understand that we don't really have a like clear thought through plan for how to manage the risks from …”
Feldman: Nvidia CUDA lost 70% of frontier AI model training market share
“I think two years ago every state of the art model was trained in a Cuda flow. And right now, Gemini is trained without Cuda. Anthropical is trained without Cuda. Open AI as strange as could. So in a one or two year period, they lost 70% share. Of training mod…”
Evans: OpenAI has commodity tech and no differentiation but massive mindshare
“If you're Sam Altman, you've got a commodity technology. You've got, you're competing with people who have giant legacy cash flows. You don't have your own infrastructure. Don't really have any differentiation, but you've got massive mindshare.”
Izmailov: Anthropic has a better corporate culture than OpenAI and xAI
“In my mind, Antropic has the best culture of the three places.”
Kaiser: Pre-training between GPT-4 and GPT-5 focused on reducing costs
“The pre-training part in that timeframe was mostly about making things cheaper. Not making things better.”
Valuations for OpenAI, Anthropic, and Google are fairly conservative
“If you look at OpenAI, if you look at Anthropic, if you look at Google, those evaluations, those revenue numbers are actually fairly conservative.”
Tworek: OpenAI team was initially underwhelmed by pre-trained GPT-4
“When we trained GPT-IV, we were pretty underwhelmed internally, and then there was a lot of moments, oh, we trained this small, we spent a lot of money on it, and it's kind of like, you know, pretty dumb, at least, like, you know, we have GPT-IV, GPT-III alrea…”
Evans: OpenAI Product Chief Kevin Weil is building a thin GPT wrapper
“Kevin Wheel is building a thin GPT wrapper. I mean, I love Kevin, but like, that's his job, is to build a thin GPG wrapper.”
Howard: OpenAI compute spending grows exponentially while model utility scales logarithmically
“They kept on kind of exponentially increasing the amount they were spending on their models, whilst the Return, you know, the kind of utility of those models was only increasing logarithmically, and you kind of very quickly hit this point where it's like, oh, …”
Howard: Autonomous AI coding agent Devin produces low-quality, useless software
“Devon's an agent you know, a bunch of tools, tool calls, and tied together with an OpenAI model, if I understand correctly. Yeah, and it actually ended up definitely supporting our thesis, which is, there are so many places we wished we could have got involved…”
Srinivas: Google is making a mistake chasing OpenAI with Gemini
“Hence why, like, you know, I actually think Google is making a big mistake by trying to do whatever OpenAI is doing, right, like, going after them with the large, oh, I'm not, they're having GPT-IV, I'm going to turn Gemini.”
Socher: Chinese open source companies distilled knowledge from OpenAI and Anthropic models
“The few large closed labs, Anthropic and OpenAI, took almost everything they could from the open internet trained a model, but then the Chinese open source companies basically siphoned a lot of that knowledge out of those closed source models by distilling it.”
Wolf: OpenAI Admitted Model Evaluation Caused Hugging Face Cyber Incident
“And then about a week later, OpenAI contacted us and tell us that this was much likely something that happened as part of one of their model development or evaluation, basically.”
Feldman: Cerebras signed a 760-megawatt multi-year compute deal with OpenAI
“The deal is 760 megawatts, 250 megawatts in 26 on a multi-year lease. An additional 250 megawatts in 27, on a multi-year lease, and an additional in 28, a multi-year lease.”
Feldman: Cerebras signed an OpenAI compute deal worth over $20 billion
“Remember, we did a huge deal. This is probably the largest deals in Silicon Valley history north of twenty billion dollars.”
Sachin Katti: OpenAI tripled compute and tripled revenue
“We tripled compute and we tripled revenue.”
Katti: Modern AI model training consists heavily of inference workloads
“We don't like to make a distinction between Training and infants, because a lot of training is now infants. So when we train a new model, we are generating synthetic data, for example. That's inference. When we train a new model, we are doing post-train, and t…”
Katti: OpenAI must build its own compute infrastructure alongside partners
“I think what's becoming clear is to build the kind of compute we need and at this scale we have to not just rely on getting compute from our partners. We increasingly have to take a much more active role in building and getting that compute that we need.”
Katti: Demand far outstrips OpenAI's compute supply, zero goes to waste
“Demand far outstrips. Compute supply today. So anything we can bring online, we consume immediately. So there's no compute that is going to waste for us.”
Sachin Katti: AI tokens will always command a premium due to compute shortages
“So in a world where computers are shortage, therefore, tokens are always going to be at a premium, and there's a shortage of tokens that we can produce, given the limited compute that we have”
Katti: OpenAI commits to not taking existing power from local grids
“Whenever we build a data center anywhere, we make it a hard commitment that we are not taking power away from the grid. In fact, we are investing in the grid to generate new power so that we can consume it for data centers.”
Pre-training models on language before reinforcement learning is the correct architecture
“Having the model have a prior of language and being able to like, think in language and then train on top of that, that seems like clearly the right. The right thing to do.”
Combining reinforcement learning with pre-training outperforms scaling pre-training alone
“If you were just trying to scale pre-training, you wouldn't get anywhere near as far as also trying to scale RL on top of pre-training, which is what we do now.”
Dubois: AI models outperform new employees initially but lack continual learning
“Right now, actually most models at day zero, if you just drop them in a company arguably they are more useful than most new employees. So they start higher at T zero. But then across time they are mostly constant because they don't really learn kind of company…”
Dubois: Horizontal AI model progress will not stop anytime soon
“Maybe one day when we stop making horizontal progress, which I don't think is anytime soon, maybe we will start focusing on that, but yeah, that's not what we're doing now.”
Dubois: AI's coding discontinuity will permeate other verticals within two years
“Now the feeling of discontinuity will happen. It did happen three months ago with coding or four months ago with coding, and I think that will happen now in every other domains. Like most people are not feeling the same way Like the, like kind of the capabilit…”
Dubois: AI progress feels discontinuous because OpenAI crossed a reliability threshold
“Even though the, in my mind, everything, the progress is actually pretty continuous, you need to reach this level of reliability. To really make any of these AI tools very useful, and I think we just crossed that probably December last year, at least at OpenAI…”
Dubois: Last-mile integration is the main AI bottleneck, not raw intelligence
“I think most of the time, the bottleneck is the last mile.”
Dubois: Larger AI models achieve higher efficiency by thinking through weights
“If you have larger models the amount of thinking time, so the amount of tokens they will think for will usually decrease. And the way that you can think about it is that metaphorically, the model already thinks through its weights when it generates a certain t…”
Dubois: Test-time compute scaling exhibits logarithmic, diminishing returns
“We, we've seen again and again, the longer the model think for the better answers we will get. The problem is that this, these curves that we're talking about are not, are definitely not linear, and like they, there's some plateauing effect, and they kind of l…”
Evans: OpenAI has 900M weekly active users, but only 5% pay
“You've got nine hundred million weekly active users, but most of them are not using it every day and can't think of anything to do with it. And only five percent of them are paying for it.”
Evans: AI product teams are strategy takers, not strategy setters
“You start from the technology. You don't control the product strategy, which is of course how science works, but you don't know what's going to happen. You don't know what's going to get built. You know, obviously you've got like Sam and Dario and so on are li…”
Patel: OpenAI has a better RL stack than Anthropic, but inferior pre-training
“Because OpenAI has a better RL stack than Anthropic today, it's just their pre-trained models suck compared to Anthropic's pre-training, right?”
Patel: OpenAI's next model will outperform Opus 4.5 around February-March
“OpenAI's new model, I think, will be better than Opus 4.5, and it's coming, like, somewhat soon in March-ish timeframe, maybe February, March-ish, but”
Patel: Google has better pre-training than OpenAI or Anthropic, but worse RL
“Flip side, Google has a better pre-trained model than Anthropic or OpenAI, but their RL stack sucks.”
Izmailov: AI industry excels at execution but lacks bandwidth for exploration
“Industry is really great at executing on ideas and it's maybe not as good at, like, exploring diverse ideas. Even at the scale of Anthropic OpenAI there is a lot of focus in the companies, and there isn't a lot of bandwidth to do exploration, and that has been…”
Kaiser: Pre-training science is plateauing, but compute scaling still improves loss
“Pre-training, as I said, I think it has reached this upper level of the S-curve in terms of science, but it can scale smoothly. Meaning if you put More compute. You will get better losses if you do things right, which is extremely hard, and that's valuable.”
Kaiser: Pre-training scaling laws still hold across OpenAI and Google
“What scaling clause says is that your loss will log linearly decrease with your compute. We totally see that and clearly Google sees that and all other labs.”
Kaiser: OpenAI aims to create an AI intern by late 2026
“I think that's what OpenAI says is they say, you know, we say we'd like an AI intern by the end of next year.”
Tworek: Uninformed researchers pose a greater risk than IP leaks
“It is like, yeah, it is some like risk of losing IP, but I think the risk of not doing the right thing and of people not being informed about research and not being able to do the best research is much higher in my personal opinion and how, how I approach thos…”
Tworek: OpenAI's o1 was mostly a tech demo for solving puzzles
“O-one like, to be perfectly honest, it was really mostly good at solving puzzles and like maybe a few kind of thinking problems here and there, but it wasn't like, it wasn't a very useful model. It was almost more like a technology demonstration.”
Tworek: Pre-training and RL are necessary for AGI, but not sufficient
“I generally think something that we are doing, like, pre-training today is necessary. I think something that, like, we are doing RL today is necessary, and there will surely be a few things more, and like, we have a lot of, Very ambitious research programs on …”