reasoning models

“We've just scratched the surface at the moment. It's mostly focused on, you know math problems and this sort of thing. There is a whole world of applications that we need to make it work work in medicine, you know, everything from the pure sciences, physics, c…”

“It's easy to create a reasoning model. It's dramatically cheaper than pre-training. And so it's accessible. And so there's this huge intelligence uplift that comes for really quite little effort.”

“One point was, of course, the Transformers when it started, but the other point was reasoning models.”

“So currently, and current for at least the Most basic ways we use it currently, it needs to be fairly verifiable. So there is an, is your answer correct or not? You prepare data for that. You can do that in mathematics, coding very well. You can do this in sci…”

“So we started working on it maybe three years ago”

“Using more tokens to think increases your capability, and it increases it, given the computation, way faster than pre-training, right?”

“Reasoning is a big priority”

“Reasoning models were the next big breakthrough. Those are rare. They do take kind of a, you know, both, both a massive scale and kind of a bit of luck to get there.”

“Reasoning models were much more effective because you can't really do the same trick of optimizing for a probability with a reasoning model that has a whole trace of reasoning that happens in the middle and kind of reflect a bit more. So it's much harder to br…”