The more Hacker News worthy discussion is the part where the author talks about search through the possible mini-program space of LLMs.
It makes sense because tree search can be endlessly optimized. In a sense, LLMs turn the unstructured, open system of general problems into a structured, closed system of possible moves. Which is really cool, IMO.
Yes! This seems to be a really neat combination of 2010's Bayesian cleverness / Tenenbaumian program search approaches with the LLMs as merely sources of high-dim conditional distributions. I knew people were experimenting in this space (like https://escholarship.org/uc/item/7018f2ss) but didn't know it did so well wrt these new benchmarks.
