
David Pfau
21.9K posts

David Pfau
@pfau
Knowledge manifests itself in radiant dreams that shimmer like the wild sun Views are my own https://t.co/xqtVHHVI17 on 🦋



there's a truly bonkers hot mic moment at the end of this that may change the way you think about anthropic you're gonna want to read all the way through this one vanityfair.com/news/story/dar…





there's a truly bonkers hot mic moment at the end of this that may change the way you think about anthropic you're gonna want to read all the way through this one vanityfair.com/news/story/dar…






there's a truly bonkers hot mic moment at the end of this that may change the way you think about anthropic you're gonna want to read all the way through this one vanityfair.com/news/story/dar…

We need a grand unification between physics and computer science to understand the relationship between energy and information. Always nice to see work that brings them together.

I’ve been at a small conference this week, one where the AI people have been presenting early in the week and the domain science people will be presenting later in the week. At the end of the talks last night, the conversation turned very doomer with all the AI people talking about how well Claude Code or Codex can do hill-climbing AI research and how we (the AI people) are maybe all about to lose our jobs! The domain science people expressed their shock at this attitude because, though Claude Code can be let loose to complete lots of banal hill-climbing AI research projects, basically no experimental science is hill-climbing or even metric driven. Most scientific fields are about much more taste-driven exploration that is incredibly difficult to make metrics for or to parameterize, and this misunderstanding from the AI community is one of the most damaging things to the realization of great science with AI. Seems like we’re actually pretty far from having AI models do that… Over the summer, @evijit and I wrote about this (and some other things hindering AI for science) at a bit more length, and today that work is out in Patterns! So, if you care about these problems and the real challenges in bringing AI to science in the real work, I recommend giving it a read!






