4 ms·
Yann LeCun was saying 3 years ago that because token generation is auto-regressive, its mathematically impossible to generate a long stream of coherent tokens,
by nok22kon 3mo ago
Yann LeCun was saying 3 years ago that because token generation is auto-regressive, its mathematically impossible to generate a long stream of coherent tokens, because errors amplify exponentially.
and then models learned that they can back track and error correct
so much for "mathematically impossible..."
- charcircuit 3mo agoI think it was largely the introduction of tool calling that allowed models to mitigate the issue of errors amplifying exponentially since it allows the model to understand if what it generated is correct or has issues that it needs to address. This addresses the potential lack of or low quality of world model by being able to reference the current state of the world.
- ravenstine 3mo agoI've definitely realized this phenomenon after a few occasions of erroneously trying to rely purely on instructions to get an LLM to do a thing or take on a role, especially without persistent cloud-based sessions that have internal checklists and other opaque guidance. They're essentially poor at self-managing, but can do really well when they are limited in scope/context and are worked into a sort of state machine that guarantees they perform certain tasks predictably. They won't always do those tasks the exact way you expect them to, but at least they actually do them, and because of that they are more likely to have the correct prior context to perform the next task better. Because they are so prone to selectively ignoring directions, that can quickly send them down an incorrect path that compounds on itself.
- jiggawatts 3mo agoAlso, almost any argument against LLM intelligence also applies to humans. I very commonly see someone make some small mistake and end up going in the wrong direction, “accumulating stupid” as they go, sometimes for years.
- fragmede 3mo agoAlso with the stochastic parrot thing. If you say just the right thing to the right human and the right time, they'll very predictibly say their favorite movie/book quote or song lyric, like some sort of parrot.
- dgellow 3mo agoAn LLM will tell you how a song feels, even if it has literally no way to experience music. Because it's not thoughts or feelings that you get from an LLM. We take a massive amount of information, compress it into a large graph, then explore sections of the graph via prompts. That's what the stochastic parrot means. And that doesn't compare with how humans think. It's just a completely different architecture
- zulux 3mo agoThe trouble is that a 24/7 AI stochastic parrot does pretty damn well at some things. In my estimation, we're arguing about how big the blast radius will be.
- jhbadger 3mo agoAnd also, if you put an actual parrot in a room full of programmers, it might learn a few word of programming jargon, but it never will become a useful coding partner the way LLMs are.
- shevy-java 3mo agoHumans can learn. AI can not. For those disagreeing: please explain how a static hardware can learn.
- threethirtytwo 3mo agothis is profoundly false. AI not only can learn, it is built entirely from learning. The field is called machine learning after all. Not only that... AI is NOT only learning during the training phase... LLMs learn in real time the minute you talk to it. It learns something and saves those learnings in a context window or somewhere else if you want it to exist beyond the context window. All of the above runs on static hardware. Don't understand how someone can say a profoundly wrong statement and get voted up.
- waldarbeiter 3mo ago[dead]
- TMWNN 3mo ago> and then models learned that they can back track and error correct You mean "Human developers learned ...", yes? Or was there really an all AI-driven, self-improving aspect to this?
- shevy-java 3mo agoYou insinuate here AI "learned". I doubt that this was AI self-improvement.
- rcxdude 3mo agoWas there a particular change to the network or the way that it was trained that introduced the 'backtrack and error correct' mechanism?
- deleted 3mo ago[deleted]
- infinite_spin 3mo agodo you have a problem with this field of research being called "machine learning"?
- aswegs8 3mo agoDoes that take anything away from the argument?
- card_zero 3mo agoWhat argument, "a theory was wrong"? No, the inane central observation, the observation that a researcher was unable to predict a discovery before it was discovered, remains true despite the gratuitous insertion of a little bit of bullshit about AI learning. I suppose it's additionally trying to imply something else, like "due to a pattern of researchers being unable to discover discoveries before they discover them, AGI is just around the corner".
- nok22kon 3mo agoits one thing to say "we dont know" it's a different thing to say "it's mathematically impossible" so if it turns out it is possible, what then? was math broken? or the researcher an idiot who either doesnt know math, or is just bullshitting non-existing proofs?
- threethirtytwo 3mo agoStop attacking Yann. I would say like 90% of the HN crowd was parroting Yann too.