Maybe I’m misunderstanding something. The way I read the results, I understand it like this - you give Astra “a bunch of numbers”, and tell it - “hey, this is a net trained on some game? What game is that?” And Astra goes - “Breakout, no doubt!”

To me this is fundamentally different from having ingested a bunch of docs so it now “knows Java” in its weights.

Ah, ok, so basically advanced pattern matching. I wonder if they train models on each other's weights?

that would imply the learning of what the weights mean can be done unsupervised which is really cool.

it probably has however been trained on papers talking about ways they extracted subsets of LLMs as say, the part that knows chess, and would be able to then use similar commands to process the weights