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Predicting the next word requires understanding, they're not separate things. If you don't know what comes after the next word, then you don't know what the nex
by energy123 1y ago
Predicting the next word requires understanding, they're not separate things. If you don't know what comes after the next word, then you don't know what the next word should be. So the task implicitly forces a more long-horizon understanding of the future sequence.
- IAmGraydon 1y agoThis is utterly wrong. Predicting the next word requires a large sample of data made into a statistical model. It has nothing to do with "understanding", which implies it knows why rather than what.
- orionsbelt 1y agoIlya Sustkever was on a podcast, saying to imagine a mystery novel where at the end it says “and the killer is: (name)”. Saying it’s just a statistical model generating the next most likely word, how can it do that in this case if it doesn’t have some understanding of all the clues, etc. A specific name is not statistically likely to appear
- shwaj 1y agoCan current LLMs actually do that, though? What Ilya posed was a thought experiment: if it could do that, then we would say that it has understanding. But AFAIK that is beyond current capabilities.
- krackers 1y agoSomeone should try it and create a new "mysterybench". Find all mystery novels written after LLM training cutoff, and see how many models unravel the mystery
- IAmGraydon 1y agoIt can't do that without the answer to who did it being in the training data. I think the reason people keep falling for this illusion is that they can't really imagine how vast the training dataset is. In all cases where it appears to answer a question like the one you posed, it's regurgitating the answer from its training data in a way that creates an illusion of using logic to answer it.
- CamperBob2 1y agoIt can't do that without the answer to who did it being in the training data. Try it. Write a simple original mystery story, and then ask a good model to solve it. This isn't your father's Chinese Room. It couldn't solve original brainteasers and puzzles if it were.
- dyauspitr 1y agoThat’s not true, at all.
- IAmGraydon 1y agoPlease…go on.
- stevenhuang 1y agoYou sound more like a stochastic parrot than an LLM does at this point.
- squigz 1y agoThis implies understanding of preceding tokens, no? GP was saying they have understanding of future tokens.
- nicpottier 1y agoI once was chatting with an author of books (very much an amateur) and he said he enjoyed writing because he liked discovering where the story goes. IE, he starts and builds characters and creates scenarios for them and at some point the story kind of takes over, there is only one way a character can act based on what was previously written, but it wasn't preordained. That's why he liked it, it was a discovery to him. I'm not saying this is the right way to write a book but it is a way some people write at least! And one LLMs seem capable of doing. (though isn't a book outline pretty much the same as a coding plan and well within their wheelhouse?)
- astrange 1y agoIf you're claiming a transformer model is a Markov chain, this is easily disprovable by, eg, asking the model why it isn't a Markov chain! But here is a really big one of those if you want it: https://arxiv.org/abs/2401.17377 https://arxiv.org/abs/2401.17377
- nl 1y agoModern LLMs are post trained for tasks other than next word prediction. They still output words through (except for multi-modal LLMs) so that does involve next word generation.
- Workaccount2 1y ago"Understanding" is just a trap to get wrapped up in. A word with no definition and no test to prove it. Whether or not the model are "understanding" is ultimately immaterial, as their ability to do things is all that matters.
- pinnochio 1y agoIf they can't do things that require understanding, it's material, bub. And just because you have no understanding of what "understanding" means, doesn't mean nobody does.
- red75prime 1y ago> doesn't mean nobody does If it's not a functional understating that allows to replicate functionality of understanding, is it the real understanding?
- dyauspitr 1y agoThe line between understanding and “large sample of data made into a statistical model” is kind of fuzzy.
- HarHarVeryFunny 1y ago> Predicting the next word requires understanding If we were talking about humans trying to predict next word, that would be true. There is no reason to suppose than an LLM is doing anything other than deep pattern prediction pursuant to, and no better than needed for, next word prediction.
- CamperBob2 1y agoHow'd you do at the International Math Olympiad this year?
- HarHarVeryFunny 1y agoI hear the LLM was able to parrot fragments of the stuff it was trained to memorize, and did very well
- CamperBob2 1y agoYeah, that must be it.
- cxvrfr 1y agoWell being able to extrapolate solutions to "novel" mathematical exercises based on a very large sample of similar tasks in your dataset seems like a reasonable explanation. Question is how well it would do if it was trained without those samples?
- CamperBob2 1y agoGee, I don't know. How would you do at a math competition if you weren't trained with math books? Sample problems and solutions are not sufficient unless you can genuinely apply human-level inductive and deductive reasoning to them. If you don't understand that and agree with it, I don't see a way forward here. A more interesting question is, how would you do at a math competition if you were taught to read, then left alone in your room with a bunch of math books? You wouldn't get very far at a competition like IMO, calculator or no calculator, unless you happen to be some kind of prodigy at the level of von Neumann or Ramanujan.