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 6 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
Huber: LLMs are like CPUs, not operating systems
“I don't think of an LLM as an operating system. I think an LLM is much more like a CPU, right? It's an information processing unit.”
Huber: Open-source models win B2B through developer focus, not beating GPT-5
“Focus on the developers. I think that's the beachhead. That's how you win the B to B market. If you win the B to B market with your open source models, Like, you get all of the sort of downstream effects that you want. You know, you don't need to beat you know…”
Huber: Language models require a multi-tiered memory hierarchy like traditional computers
“In the same way that we have a memory hierarchy in classic computers, right, we have the CPU, RAM, disk, and network we are also going to have a similar memory hierarchy in language models. And again, it already exists today. We have the actual sort of transfo…”
Huber: Fine-tuning model weights fails enterprise AI due to lack of deterministic control
“Updating the weights of the model is not a very good idea because you cannot really deterministically control that. You can fine tune, but what you're going to get the other end, you know, again, you don't really control.”
Huber: Model releases often top leaderboards but lack practical developer hooks
“You know, you see a lot of like model drops that come out, but they don't actually provide the real hooks and they do very well in the benchmarks, right? They do very well on like kind of the public leaderboards. But they don't actually provide the hooks that …”
Huber: Fuzzy search is most useful when users don't know the dataset
“Fuzzy search is really useful when people like are not, you know, experts in their own data, right? Is that if you're Google Drive, you know how to search for stuff pretty well, right? But like your users don't know how to search for the stuff that you've said…”