George Cameron: belief

Transcript context

…I’ve looked at those numbers. I calculated them. I don’t remember. Yeah. But I remember thinking like, this must be it. Your 5% is exactly like around the ballpark for the open weights models of, of what’s released today. I think one interesting that gives me kind of pause when thinking that it won’t go, the sparsity won’t go high. Or the number of percentage of active parameters lower is that we, in our benchmark, see a lot of performance, uh, correlated more with, uh, total parameters than active and not that correlated with how sparse, like the models are. Our accuracy, benchmark as part of a omniscience, it’s very correlated with total. It’s not correlated with, with active, uh, parameters, which I think is very at all, which is very, very interesting. And so I think, yeah, they could, they could be quite. A bit, um, to go here. Awesome. Well, we don’t have that much time, but I w I did want to leave some room to cover reasoning and non-reasoning models and token efficiency. Let’s do that. So at a high, at a super high level, people have to classify this binary thing of reasoning versus non-reasoning. People who are insider have some discomfort with that because basically you just have to think tag or no think tag. How have you guys decided to approach this? And also how does that laid out in, over the course of the year where we have things like GPT-5, which is a model. Right.…

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