The speaker describes a view that models are not trained to find certain connections, but that an RL environment incentivizing this behavior might require relatively little additional compute.

“i was asking scott about this the other day when i interviewed him scott alexander and he said like look humans also don't have this kind of logical omissions i'm not saying more omniscient but we have examples of humans finding these kinds of connections this is not an uncommon thing right i think his response to that was that these things are just not trained in in order to find these kinds of connections but if you if you like their view is that it would not take that much extra compute in order to build some rl environment in which they're incented”

“are incentivized to find these connections next token prediction just isn't incentivizing them to do this but the rl required to do this would not be that or set up some sort of scaffolds i think actually google deep mind did do some similar like scaffold to make new discoveries and i didn't look into like how impressive the new discovery was they claim that some new discovery was made by an llm as a result um”