That's the sorcery mentioned in the GP, the issue comes when people believe it to be smart however in reality it is just a next word prediction. Gives the impression it's actually thinking, and this is by design. Personally I think it's dangerous in the sense it gives users a false sense of confidence in the LLM and so a LOT of people will blindly trust it. This isn't a good thing.
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You cannot predict all the actions or words of someone smarter than you. If I could always predict Magnus Carlsen's next chess move, I'd be at least as good at chess as Magnus - and that would have to involve a deep understanding of chess, even if I can't explain my understanding.
I can't predict the next token in a novel mathematical proof unless I've already understood the solution.
If you can predict the words a bright person will say about X... Isn't that some truly astounding tool? That could be used in myriad useful ways if one is a little creative with it
Since it's also "alien" it can also detect and explore paths that we simply haven't noticed since their biases aren't quite the same as ours
So I think "word predictor" makes sense here. A word predictor can be really really cool.
There is no design of such a machine that does not encode a very deep understanding of the game.
Leela Chess Zero does understand chess. She plays at roughly 2300 strength with a search depth of 1 ply - purely on the strength of her gestalt evaluation of the position. Humans have learned a lot about chess from studying her (and AlphaZero’s) games. General, transferable knowledge she developed herself about - for example - the long term value of early rook pawn advances.
“Understanding” doesn’t imply anything about personhood or self reflection or awareness.
I have no idea how Magnus Carlsen "understands" chess. Neither does anyone else. His brain is giant neural net, taking inputs, sending signals around, and coming out with an output. We think we understand the mechanics of this, but we do not understand exactly why or how sending these signals around produces such good outputs.
So to argue you know for certain that an LLM is not intelligent because it is "just" a next token predictor, without knowing if that is how the human brain operates, is thinking too highly of yourself.
"In almost any other application, the biggest Achilles heel of AI is that it makes unverifiable mistakes. But in mathematics, almost uniquely, you can automatically check the output — at least if the output is supposed to be the proof of a theorem, although that is not the only thing mathematicians do. So, AI companies have recognized that their most unambiguous successes — if they’re going to have any — are going to come from mathematics.
In my opinion, there are many use cases of AI that are risky and controversial. In mathematics, the downsides are much more limited
"AI successes in mathematics don't generalize to successes in other fields as the AI promoters want to suggest.
I knew how LLMs work since 2019 and I've been testing their capabilities. I believe they actually are smart in every meaningful way.
"Next word prediction" just means that answer is generated through computation. I don't think computation can't be smart.
If you believe that LLMs are probabilitic and humans aren't, how do you explain randomness in human behavior? E.g. people making random typos. Have you ever tried to analyze your own behavior, understand how you function? Or do you just inherently believe you're smarter than any computation?
What would it take for you to concede a future model was smart?
For example, it's training set it purely engineering and code with general language data set, would be "aware" what art is, but has never seen an artistic image, aware what colours are and able to create something it never saw before.
Like a child with a paintbrush, there is an intuitive behavior that happens.
They can already create something they've never seen - you can prompt ChatGPT to generate images, and there's a few dedicated models for it: https://chatgpt.com/images/
Terence Tao feels like they've done innovative work on mathematics: https://www.scientificamerican.com/article/amateur-armed-wit...
