[riffraff]

Yeah, it seems as if he has forgotten the G.

I recall Norvig's AI book preaching decades ago that "intelligent" does not mean able to do everything, and that for an agent to be useful it was enough to solve a small problem.

Which in my mind is where the G came from.

And yet we now suddenly go back to the old narrow definition?

I still see no path from LLMs and autonomous driving to AGI.

[m-i-l]

> "Yeah, it seems as if he has forgotten the G. ... I still see no path from LLMs and autonomous driving to AGI."

That is exactly my view too. While LLMs and autonomous driving can be exceptionally good at what they do, they are also incredibly specialist, they completely lack anything along the lines of what you might call "common sense".

For example, (at least last time I looked) autonomous driving largely works off object detection at discreet time intervals, so objects can pop into and out of existence, whereas humans develop a sense of "object permanence" from a young age (i.e. know that just because something is no longer visible doesn't mean it is no longer there), and many humans also know about the laws of physics (i.e. know that if an object has a certain trajectory then there are probabilities and constraints on what can happen next).

[05]

It doesn’t look like it works off discrete frames.. https://waymo.com/research/stinet-spatio-temporal-interactiv...

[m-i-l]

Thanks, interesting read (it was a while ago I looked into this). I think the point still remains though - a self driving car doesn't have any general knowledge which can be applied to other areas, e.g. what a pedestrian is, or why a pedestrian who sees you is unlikely to step out in front of you. And similarly, the ordered tokens that an LLM outputs sometimes appear "stupid" because it has no "common sense".