Earlier quoted context omitted.
> Contrast with the way a human learns skills - as we gain experience with a skill, we get better at understanding when it's the right tool for the job. Which is precisely why Richard Sutton doesn't think LLMs will evolve to AGI[0]. LLMs are based on mimicry, not experience, so it's more likely (according to Sutton) that AGI will be based on some form of RL (reinforcement learning) and not neural networks (LLMs). Mor…
It's a false dichotomy. LLMs are already being trained with RL to have goal directedness. He is right that non-RL'd LLMs are just mimicry, but the field already moved beyond that.
That might be true, but we're talking about the fundamentals of the concept. His argument is that you're never going to reach AGI/super intelligence on an evolution of the current concepts (mimicry) even through fine tuning and adaptions - it'll like be different (and likely based on some RL technique). At least we have NO history to suggest this will be case (hence his argument for "the bitter lesson").