> 3. how can a set of (hypothetical) neurons be arranged so as to form concepts.
> 6. machine methods of forming abstractions from sensory and other data.
Still unsolved after 66 years, the problem indeed "needs more theoretical work".
Working on these at the same time with designing computer and compiler (1 & 2) probably was a big distraction.
Another distraction is introducing 5 & 7 ("self-improvement" and "randomness & creativity") before answering more fundamental questions of knowledge representation (3 & 6).
Kind of like building algorithms before figuring out the details of data structures.
I feel the context has to be emphasized here. FORTRAN won't appear until a year later and LISP for all three. It was no distraction: it was so early that much of CS and computing history branches out from that event.
yes, that project was so influential in developing computer science, it determined almost all subsequent AI efforts from symbolic AI to the recent revival of ANNs.
Those influential 1950s seminars contributed to the current treatment of AI as a subset of CS instead of independent discipline with roots in cognition and neuroscience research.
but with all due respect you can’t really talk about artificial intelligence before understanding intelligence
To me, an interesting bit of trivia is that Cognitive Science had its own introductory moment just a few months later at MIT with some overlapping attendance. This is particularly of note if you aren't of the school of thought that AI ~ ML. But cognitive science hasn't had its own equivalent period of rapid advance.
Short answer is probably not really. McCarthy was at Dartmouth very briefly which happened to overlap this conference. He moved on to MIT and then Stanford.
John Kemeny was recently in Dartmouth's math department at the time but AFAIK there was very little interaction with the early AI work.
> 6. machine methods of forming abstractions from sensory and other data.
Still unsolved after 66 years, the problem indeed "needs more theoretical work".
Working on these at the same time with designing computer and compiler (1 & 2) probably was a big distraction.
Another distraction is introducing 5 & 7 ("self-improvement" and "randomness & creativity") before answering more fundamental questions of knowledge representation (3 & 6).
Kind of like building algorithms before figuring out the details of data structures.