Earlier quoted context omitted.
If that's the case, then, what's the wall? The "walls" that stopped AI decades ago stand no more. NLP and CSR were thought to be the "final bosses" of AI by many - until they fell to LLMs. There's no replacement. The closest thing to a "hard wall" LLMs have is probably online learning? And even that isn't really a hard wall. Because LLMs are good at in-context learning, which does many of the same things, and can do…
Agree completely with your position. I do think though that lack of online learning is a bigger drawback than a lot of people believe, because it can often be hidden/obfuscated by training for the benchmarks, basically. This becomes very visible when you compare performance on more specialized tasks that LLMs were not trained for specifically, e.g. playing games like Pokemon or Factorio: General purpose LLMs are lagg…
Pre-training a base model on text datasets teaches that model a lot, but it doesn't teach it to be good at agentic tasks and long horizon tasks.
Which is why there's a capability gap there - the gap companies have to overcome "in post" with things like RLVR.