Llion Jones: evaluation

Transcript context

…We just released the Continuous Thought Machine. It's a spotlight at NeurIPS 20 25 this year. You should care about it because it has native adaptive compute. It's a new way of building a recurrent model that uses higher level concepts for neurons and a synchronization as a representation that lets us solve problems in ways that seem more human by being biologically and nature inspired. The atmosphere in AI research was actually quite different back during the Transformer years, because it doesn't feel like something similar could actually happen right now because of the reduced amount of freedom that we have. Right? The Transformers was very, very bottom up. Right? It's not that somebody had this grand plan that came down from 1 high that this is what we should be working on. It was a bunch of people talking over lunch, thinking about what the current problems are and how to solve them, and having the freedom to have, you know, literally months to dedicate to just trying this idea and having this this new architecture fall out. We've spent hundreds of millions of dollars. The biggest sort of evolution based search is probably in the tens of thousands. We have all this compute. What happens? What happens if you scale up these search algorithms? And I'm sure you will find something interesting, you know, when someone eventually does buy that bullet and really scale up these evolution ary sort of a life experiments. Because I pitched it in an environment where people were just going all in on this 1 technology, I got 0 interest. So now I have my own company, and I can pursue those directions. This podcast is supported by CyberFund.…

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