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 876 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 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
Arora: Product managers are effectively glorified UI managers
“Product managers are effectively glorified UI managers, so we're trying to make sure that us common folks can interact with data and some sort of engineering algorithm behind it because we're not smart enough to talk to the engineering algorithm ourselves.”
Liemandt: Skipping Multiplication Table Memorization Dooms Students in Advanced Math
“If you're an advanced math problem, and you're doing seven times eight, and seven times eight to you is still a calculation. Right? You're doomed, right? There's just, there's no way around it. You'll start making careless errors.”
Liemandt: Critical Thinking Impossible Without First Imparting a Factual Base
“If you don't give them a fact base, then their opinions are just making stuff up. You have to reason over a fact base.”
Nadler: Psychoanalyzing the trauma behind your motivation destroys your propulsion system
“I mean, I think there's a lot of truth to that except you don't want to go too close to that stuff because you'll actually kill the propulsion system in analyzing it.”
Patel: Hyperscalers cannot replicate CPU and storage profit margins in GPUs
“Their ROIC is, like, extremely high on CPU and storage, and to assume that it can, like, translate over to GPUs is, is a bit of a fallacy, which is why a lot of these companies are moving in, right?”
Laskin: New frontier labs can succeed without cloud provider ownership
“Our thought was that this was the time where you can actually start a you know, a generational frontier lab that does not need to be coupled to a, you know, to a big cloud provider because if you do it right, you'll actually be able to generate you know, suffi…”
Laskin: Machine learning generalization is just bringing test distribution into training
“There's no such thing as generalization. There's just bringing the test distribution into train.”
Parker Conrad: Founders learn far more from success than failure
“There's this sort of like idea in Silicon Valley that you should learn a lot from failures. And I, I'm not sure that I agree a lot with, I think that actually people probably learn a lot more from their successes and, you know, companies fail for like, Many du…”
Hendrycks: Voluntary AI Pauses Without Enforcement Only Benefit Bad Actors
“If you do it voluntarily, you just make yourself less powerful and you let the worst actors get ahead of you. You could say, well, we'll try and try to sign a treaty. We will not assume that the treaty will be followed. Like that would be very imprudent. You w…”
Hendrycks: AI Safety Is a Geopolitical Problem, Not Primarily a Technical One
“Safety isn't, as I've been I'm trying to reinforce not really that much of a technical problem. This is more of a complex geopolitical problem with technical aspects.”
Alidoust: Hypothesis-driven biology slowed progress, but falling costs enable unbiased data
“One thing that has been a Has been slowing the progress in bio is the fact that we have always been super hypothesis driven, and I think it has, the reason is that a lot of these experiments are expensive, you know, that they take a lot of time, a lot of resou…”
Vogt: Founding a Startup to Commercialize PhD Research Is a Red Flag
“They will leave their academic program because they want to commercialize their research, which to me is like a huge red flag, because that means you are, you're saying, I'm not going to be flexible on how I solve the problem. I'm going to force my solution in…”
Torres: Paul Graham's 'do things that don't scale' rule is obsolete
“I think I want to challenge like Paul Graham says, do things that don't scale. I think that that's game over for that statement, right? I think now we only have to do things that scale.”
Khan: Antitrust evolved from broad structural metrics to narrow short-term price effects
“And so the SA was a way to use Amazon as a way to tell a broader story about the history of our antitrust laws and how we had evolved from you know, Viewing this issue of dominance and monopolization through a broader prism and a broader understanding of the d…”
Knoop: Legislating AI research from theoretical capability predictions is dangerous
“I think it's incredibly dangerous to try and make predictions about future capabilities, about where the technology will go and make rules, legislations, laws.
Like prohibiting or enforcing or requiring certain research directions through a theoretical lens.
I…”
Mensch: AI base models should know everything and use modular guardrails
“Assuming that the model should be well behaved is, I think, a wrong assumption. You need to make the assumption that the model should know everything. And then on top of that, have some modules that moderate and guardrail the model.”
Reid Hoffman: Calls for a Global Six-Month AI Pause Cannot Work
“You don't set up a flare and say, everyone should pause for six months. Oh, look, eight billion people paused. On your theory of the universe, the UN would be a highly functioning organization that we would all use for a whole bunch of things. It doesn't work.”
Hoffman: AI cannot be built by UN committees, academics lack building experience
“And you just can't have AI built by UN committee. It just doesn't exist. And it's one of the things that academics mostly don't understand because they've never, most of them, not all, of course, but most have never built anything, don't really understand how …”
Slootman: High-intensity cultures naturally filter out employees lacking the company's DNA
“Culture shorts and sifts. You attract the right ones and you start losing the wrong ones. So it's actually quite perfect. If people are leaving, they're just not your DNA. They're not your blood type.”
Aravind Srinivas argues AI application builders understand LLMs better than trainers
“The people who use the LLMs for building stuff, Understand it better than the people who actually did gradient descent and train these models.”
Inference-time compute is the missing scaling dimension for AI reasoning
“This is why I'm interested in the reasoning direction, because I think there's this whole other dimension. That people are not scaling right now, which is the amount of compute at inference time.”
Ehrlich says forward-deployed engineers are essential for fast enterprise AI adoption
“Now it seems that you're coming to a large legacy enterprise. They really want to adopt the ad because they have to, the problem is they don't know how to do it. They understand that their processes are very long. There's something that takes a year or two or …”
Hodak: Vision, hearing, balance, and 1 kbps motor control unlock radical neurotech
“If you can, if you get vision, hearing, balance, and a kilobit per second of motor control, you're halfway to the matrix. And this takes you into some like really trippy interpret reinterpretations of medicine.”
Taylor: Rebooting Nuclear Requires Shifting from Civil Infrastructure to Advanced Manufacturing
“If you're going to reboot nuclear and you're actually believe in, in the atomic energy century, which I absolutely do, it's probably not going to look like what it did in the sixties. It's not going to look like civil infrastructure. Because we're not that goo…”
Taylor: Manufactured SMRs Require Development Driven by Hardware Iteration
“What was missing is that people did not realize that you're going to have to pursue that model through hardware iteration. And that's where really where Valor is unique is that Yes, we believe in SMRs. We believe in reactors that are manufactured. But we also …”
Gil: Investors are conflating market size with speed to scale
“And people Are, at least in my experience collectively, at least investing against the fact that they believe the speed is there, which is different from the market size. People are conflating the two things right now, in my opinion.”
Gil: Physical compute constraints enforce an oligopoly among leading AI labs
“Yeah, I mean, the physical compute basically reinforces an oligopoly market because what it does is it creates a ceiling On the rate of progress any single lab can get, if effectively you assume the compute is roughly pro rata across the ecosystem to the big l…”
Tang: Suburban delivery requires 300-pound autonomous vehicles, not passenger cars
“If you're trying to solve that three to five mile delivery, In dense suburbs, which is where most of the deliveries happen, the right metaphor is probably a autonomous motorcycle or a scooter or a bike profile vehicle. And you know, it doesn't even be 4000 pou…”
Fang: Frontier AI models underperform tested on messy enterprise data
“It's like, okay, if you like dumb down the problem, maybe the models do well, but like for some reason, and when we actually have it, With the enterprise data and all the real stuff, it's not performing as well.”
Brown: AI benchmarks must control for test-time compute
“And so I think the proper way to, and so my claim is the proper way to evaluate the models now is you either have some kind of budget for the benchmark, whether it's tokens or cost or time or whatever, or you plot the performance as a function of the amount of…”
Brown: Scaffolding Easily Inflates AI Benchmark Scores Without Real Gains
“It's really easy to show you can do much better than previous benchmarks or previous, previous models on benchmarks by just, for example, scaffolding a bunch of models together. So if you say, okay, well, we're going to, instead of just running this model once…”
Current AI safety frameworks fail to account for test-time compute scaling
“The preparedness frameworks and responsible scaling policies, they don't really account for the amount of tests I'm computed. They just say, okay, well, what's the capability of the model? The problem is we're in a world now where the capability of the model i…”
Complex task compute costs fall 10x to 100x per model release
“The model release cycle is every, every couple months we put out a new model that's even more powerful, and so the cost of disproving the Erdos unit distance gesture drops by, like, 10 or a hundred x with every model release cycle. Probably, in some cases, mor…”
Noam Brown: AI community stuck in bad equilibrium publishing static benchmark grids
“I would talk to researchers about we, it makes sense to show the benchmarks with an x-axis, whether it's tokens or cost or time, there should be an x-axis, and everybody would say, like, yeah, that makes sense, we should do that, but. Well, really, their respo…”
Tan: Chip startups should target hyperscalers on day one, even granting warrants
“The next thing is look at, it's very important from day one, you'd have to target the first customer. And usually I like the customer is hyperscale. They have the scale. If they like what you have, they're willing to pay millions of dollars next few years. And…”
Zuckerberg: Building complex biology tools requires a 10-15 year non-profit horizon
“If you're building tools that are this complicated, you kind of want to have a 10 to 15 year time horizon on, on building out these efforts. And then the scale of capital required. I mean, I guess there's no rule that said that you couldn't do it as like an in…”
Zuckerberg: AI progress requires only a couple dozen researchers, not hundreds
“In order to make progress in AI, you don't need like many, many hundreds of AI researchers or thousands or anything like that. I think you can really make progress with you know, a very strong group of a dozen or a couple dozen people.”
Nadella: Public AI benchmarks are gamed; companies need private evaluations
“Most importantly, you'll have private evals because we know all the evals out there are good, interesting, But they're not really that critical at this point because they're all can be maxed. And so the point is each company will have its own private eval.”
Nadella: Platforms must enable custom intelligence layers, not single-model worship
“That idea that you can build a platform layer that someone else can then extend out and build their own intelligence layer in this case, I think is everything right without it. Why have a developer conference? I can just come and have you all sort of just wors…”
Nadella: Enterprise customers reject outcome pricing once results materialize
“Most people love outcomes until they have an outcome, because once you have an outcome, it's like giving away royalty, right? I mean, I've talked to customers who love, you know, outcome based pricing, and I say, I'm all in until they, oh my God, like, what ar…”
Taubman: 30-40% AI efficiency gives service businesses software-like incremental margins
“What we've done with AI is when you make your existing teams 30, 40% more efficient and they can handle more customers it changes the whole mindset of the organization. Now you're growing, you look like a software company now where you're now growing with High…”
Srivastava: AI Defensibility Comes from Workflow Integration, Not Models Alone
“To the extent that that is encoded in a model, I think a lot of their business will be at risk, but to the extent that it is encoded in workflows that is where they will be able to develop mode.”
Srivastava: Startups should not do post-training before achieving product-market fit
“Hey, go find, go prove to yourself with the best in class model that you have something worth optimizing. And I think, you know, A lot of, you know, if a customer comes to us, was that meme, which was like, it was like two years ago, it feels like there's no G…”
Fedus: Intelligence is not scalar; AI shows extreme, non-intuitive spikiness
“I think one fallacy is thinking about intelligence as a scalar. We've consistently seen these systems have a very odd spikiness, and it's actually possible to architect a system that is world-class on some math domain, but then you could do some perturbations …”
Karpathy: Coding agent failures are user skill issues, not capability limits
“Even if they don't work, I think to a large extent, you feel like it's a skill issue. It's not that the capability is not there. It's that you just haven't found a way to string it together of what's available. Like I just don't, I didn't give good enough inst…”
Karpathy: Maximizing AI leverage requires removing humans from prompting loops entirely
“To get the most out of the tools that have become available now, you have to remove yourself as the bottleneck. You can't be there to prompt the next thing. You're, you need to take yourself outside
you have to arrange things such that they're completely auto…”