[stevenhuang]

Yup, that's a classic article.

My favorite is Chalmer's engine bit:

> What pops out of self-supervised predictive training is noticeably not a classical agent. Shortly after GPT-3’s release, David Chalmers lucidly observed that the policy’s relation to agents is like that of a “chameleon” or “engine”:

>> GPT-3 does not look much like an agent. It does not seem to have goals or preferences beyond completing text, for example. It is more like a chameleon that can take the shape of many different agents. Or perhaps it is an engine that can be used under the hood to drive many agents. But it is then perhaps these systems that we should assess for agency, consciousness, and so on.6

[fnordpiglet]

Yeah that’s been my thought since the beginning. We have created all sorts of agents to date that are very compelling but lack a bridge into knowledge and synthesis of complex semantics. Wiring an ensemble of the various AI models created over the last 70 years I think is the final step.