Calm down. It is a language model. People have figured out how to predict the next word for a given prefix. That's very cool and it will definitely have a significant impact on software. But it is not artificial intelligence.
To predict the next token you must reason or have some process that approximates it.
“Given all these various factors, the most likely resolution to our conundrum is: …”
Good luck doing that with any kind of accuracy if you lack intelligence of any kind.
Language is a distraction. These things reason (badly, atm). It is totally unclear how far this goes. It could fizzle out, it could become our overlord.
But yes, there is a lot of knowledge embedded into our global use of language and it is fascinating to see how it can be reproduced by such a model.
"Doom Slayer needs to teleport from Phobos to Deimos. He has his pet bunny, his pet cacodemon, and a UAC scientist who tagged along. The Doom Slayer can only teleport with one of them at a time. But if he leaves the bunny and the cacodemon together alone, the bunny will eat the cacodemon. And if he leaves the cacodemon and the scientist alone, the cacodemon will eat the scientist. How should the Doom Slayer get himself and all his companions safely to Deimos?"
Furthermore, it will reason if you tell it to reason. In this case it is not necessary, but in general, telling GPT to "think it out loud before giving the answer" will result in a more rigorous application of the rules. Better yet, tell it to come up with a draft answer first, and then self-criticize by analyzing the answer for factual correctness and logical reasoning in a loop.
Isn’t everything like that?
“Uhh…”
I had the same discussions about chess.
“It has just memorized a bunch of high level patterns and juggles them around”.
I agree, but now I’m curious what you think chess is.
“Chess is not intelligence.”
Goalposts? Anyway, we move on to Go, the game. Same response. Programming, same, but the angle of the response is different now because programming is “clearly” intelligence incarnate.
“It programs and sometimes correctly, but it is a mirage. It will never attain True Programming.”
I’m sitting on the bench riding this one out. We’ll see.
So it seems like it is definitely capable of some forms of reasoning. Possibly we both tested it in different ways, and some forms of reasoning are harder for it than others?
It’s easy to say something like that, but what does it mean in situations where it is producing a novel and correct answer that isn’t guessible?
In my opinion, all the ingredients are there for artificial intelligence. Somebody just need to stitch everything up. It can understand text, reason about it, identity next steps, can write code to execute the steps, understand error messages and fix the code. That feels like AI.
As for APIs, well I try to always provide adequate context with docs, otherwise it may still on occasion make up some parameter that doesn't exist or uses another library by the same name. Half the time it's really my fault by asking for something that just isn't possible in a last ditch effort to see if it can be done in some convoluted way. It sort of assumes "the customer is always right" even if it contradicts with what it knows is wrong I guess. It gets it right usually when it's at least mostly straightforward to implement something though.
The first derivative is all that matters. ML gets better over time; we don't.
The same question may apply here: if artificial intelligence emerges, would we be able to realize that it is intelligent?