[Kim_Bruning]

So that might depend on model, how long ago you lasted tested it, etc. I've seen llms solve novel logic problems, generate meaningful text, retain tests just fine, and simple mathematics on newer models is a lot better.

Btw if you read the actual paper that proposes the Turing test, Turing actually rejects the framing of "can machines think"; preferring to go for the more practical "can you tell them apart in practice".

[grey-area]

Yes, that’s the ‘too much confidence in humans’ bit - he didn’t count on some humans being easily fooled by prolix word generators. I’d be interested in his take on these generators but I think he’d be focussed on what was missing as well as the amazing progress we have seen.

[Kim_Bruning]

So my reading of (Turing 1950)...

> "The original question, 'Can machines think?' I believe to be too meaningless to deserve discussion."

> "the question, 'Can machines think?' should be replaced by 'Are there imaginable digital computers which would do well in the imitation game?'"

> "according to this view the only way to know that a man thinks is to be that particular man. It is in fact the solipsist point of view... instead of arguing continually over this point it is usual to have the polite convention that everyone thinks."

... is: if it's practical to say the system can give meaningful intput/output on xyz in -say- natural language; we might just go ahead and say it can think about xyz, because otherwise everyone's just going to go nuts inventing new terms every time.

grey-area!thinking, kim_bruning!thinking, pet_cat!thinking, octopus!thinking, claude_opus!thinking.

Can we leave out the '!' ? Nothing to do with fooling people. Just practical ways of dealing with the overall concept.

https://courses.cs.umbc.edu/471/papers/turing.pdf