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 19 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
Kilpatrick: Pre-Training Isn't Dead; Gains Multiply Through Post-Training and RL
“And this is why, like, I don't subscribe to the, like pre-training is, you know, dead and all that stuff, because the more work that you can do at the pre-training level, those capabilities, as you do post-training and as you give the models RL capability, it'…”
Kilpatrick: AI models now outperform humans on most vision tasks
“If you look at like multimodal, like the fact that the models can like with better, better than just from a multimodal input perspective, better than humans are at like most vision tasks, like The number of products and like things that that unlocks is like tr…”
Kilpatrick: Pushing the AI Pareto Frontier Uniquely Increases Builder Margins
“And like the margin for people building AI products actually goes up every, like the farther you push the Pareto frontier, the more money builders get to make, which is like such a interesting and like unique thing about this AI moment that I actually don't th…”
Kilpatrick: ChatGPT's consumer success was driven by its API business
“I think part of my core worldview is a lot of the reason that ChatGPT has been as successful as it has
Is because there was an API business built around it.”
Kilpatrick: Gemini 2.5 Pro Relied on Pre-Training Innovations, Not Just RL
“But I think if you look at like a, an example of this in practice, like 2.5 pro is actually an example where it wasn't just like RL scaling that made that model better. Yes, RL was part of the story, but like there was also a bunch of pre-training innovation a…”
Kilpatrick: Google's Full-Stack Control Extends From Silicon to Model Delivery
“Google controls. From a product perspective, like all the way to how the models are delivered to how the models are trained down to the silicon. So like you can make decisions assuming a bunch of those things are going to be true, which is like a lot of folks …”
Kilpatrick: Real-Time Audio and Video Is Next Major AI UX Iteration
“I don't think we've seen like across other product services, people actually invest in like real-time audio and real-time video and image stuff. And I think that's like the next iteration of the UX of how people are going to interact with AI models.”
Kilpatrick: Burdening AI users with prompt crafting is a product bug
“Yeah, I actually, my personal take on this is I think this is a bug of this current AI moment where like the, if you look at like what is the ideal case is the models and the products like pull out what they need to from the user in order to create value for t…”
Kilpatrick refuses to build AI products that require changing user behavior
“And this is maybe too like absolutist of like a product perspective, but like, I will not build a product that like we have to try to convince a consumer to change their behavior.”
Kilpatrick: In 10 years, AI interfaces will look eerily similar to texting
“And I actually think if we've, if we fast forward like. 10 years, I do think there's going to be a lot of those experiences which like look eerily similar to the way that they do today, because it's just like so ingrained in like human culture, like how, like …”
Kilpatrick: AI leaps go underappreciated without consumer product experiences
“It's actually hard to appreciate some of those moments if there isn't a product experience that brings it to life. And I actually think that's been a lot of the gap.”
Kilpatrick: Chatbot Arena captures user vibes rather than evaluating scientific truth
“Like, Ella Marina is basically capturing vibes. It's like, how do people feel about this thing? It's not scientific. They're not, like, not actually evaling that the model is saying things that are true. It's like, how do humans feel about this response?”
Kilpatrick: Large High-Demand AI Models Require Massive Inference Investments
“Especially with larger models and especially with models that have lots of demand, like there's no world where you can get away with not putting a large order of magnitude of investment into inference.”
Kilpatrick: Multimodal Foundation Models Match or Beat Domain-Specific Vision Models
“Relative to today where you can literally just write a prompt and send images or videos to the model and have it do those tasks like with basically, you know, near or better accuracy than you would get from domain specific models is absolutely fascinating.”
Kilpatrick: Screen sharing eliminates the manual context-gathering friction in AI UX
“Right now the product experience of using AI is I need to go and find all the context that's relevant for the model. And get it into this text box somewhere or get it into this list of files somewhere. And like the beautiful thing about screen sharing is like …”
Kilpatrick: Google team is exploring AI-assisted and non-AI technical interviews
“I think we've actually been looking at doing like AI assisted interviews and not AI assisted interviews. Like, I think the world needs both right now. It makes perfect sense to evaluate both.”
Kilpatrick: AI assistance creates a measurable output delta across all disciplines
“There's a delta in your output if you are AI assisted versus not across coding across every discipline right now.”
Kilpatrick: AI inference costs dropped 99% over two years
“Cost of AI down 99% over the last two years.”
Kilpatrick: Heavy Gemini 2.5 Pro Demand Forces Continuous Inference Optimization
“Our team who's Like actually working around the clock right now to make it so that people can keep scaling with 2.5 pro because there's so much demand and we're having to like, you know, as a an artifact of the constraints that we're under, like we're having t…”