lairv3d ago

ARC-AGI-3

https://arcprize.org/media/ARC_AGI_3_Technical_Report.pdf

https://arcprize.org/arc-agi/3

Show threadBeetleB2d ago

> As long as there is a gap between AI and human learning, we do not have AGI.

Back in the 90's, Scientific American had an article on AI - I believe this was around the time Deep Blue beat Kasparov at chess.

One AI researcher's quote stood out to me:

"It's silly to say airplanes don't fly because they don't flap their wings the way birds do."

He was saying this with regards to the Turing test, but I think the sentiment is equally valid here. Just because a human can do X and the LLM can't doesn't negate the LLM's "intelligence", any more than an LLM doing a task better than a human negates the human's intelligence.

Show threaddaemonologist

Or the classic from Dijkstra (https://www.cs.utexas.edu/~EWD/transcriptions/EWD08xx/EWD867...):

> even Alan M. Turing allowed himself to be drawn into the discussion of the question whether computers can think. The question is just as relevant and just as meaningful as the question whether submarines can swim.

(I am of the opinion that the thinking question is in fact a bit more relevant than the swimming one, but I understand where these are coming from.)

E.W.Dijkstra Archive: On IPW's (EWD 867)

Mar 25 at 8:27pmWeb
Show threadimiric2d ago

I've come across that quote several times, and reach the same conclusion as you.

While I share Dijkstra's sentiment that "thinking machines" is largely a marketing term we've been chasing for decades, and this new cycle is no different, it's still worth discussing and... thinking about. The implications of a machine that can approximate or mimic human thinking are far beyond the implications of a machine that can approximate or mimic swimming. It's frankly disappointing that such a prominent computer scientist and philosopher would be so dismissive and uninterested in this fundamental CS topic.

Also, it's worth contextualizing that quote. It's from a panel discussion in 1983, which was between the two major AI "winters", and during the Expert Systems hype cycle. Dijkstra was clearly frustrated by the false advertising, to which I can certainly relate today, and yet he couldn't have predicted that a few decades later we would have computers that mimic human thinking much more closely and are thus far more capable than Expert Systems ever were. There are still numerous problems to resolve, w.r.t. reliability, brittleness, explainability, etc., but the capability itself has vastly improved. So while we can still criticize modern "AI" companies for false advertising and anthropomorphizing their products just like in the 1980s hype cycle, the technology has clearly improved, which arguably wouldn't have happened if we didn't consider the question of whether machines can "think".