Earlier quoted context omitted.
That's the difference though. I know my world model is fundamentally incomplete. Even more foundationally, I know that there is a world, and when my world model and the world disagree, the world wins. To a neural network there is no distinction. The closest the entire dynamic comes is the very basic annotation of RLHF which itself is done by an external human who is providing the value judgment, but even that is abse…
>I know my world model is fundamentally incomplete. Even more foundationally, I know that there is a world, and when my world model and the world disagree, the world wins. Yeah this isn't really true. There's not how humans work. For a variety of reasons, Plenty stick with their incorrect model despite the world indicating otherwise. In fact, this seems to be normal enough human behaviour. Everyone does it, for somet…
I disagree with Geoff Hinton regarding "glorified autocomplete"
191–200 of 279 posts
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#192Earlier quoted context omitted.
The difference is that "the world" is not exhaustible in the same way as Go is. While it's surely true that the number of possible overall Go game states is extremely large, the game itself is trivially representable as a set of legal moves and rules. The "world model" of the Go board is actually just already exhaustive and finite, and the computer's work in playing against itself is to generate more varied data with…
What if we are just the result of a ml network with a model of the world?
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#193Earlier quoted context omitted.
This doesn't seem like a major difference, since LLMs are also choosing from a probability distribution of tokens for the most likely one, which is why they respond a token at a time. They can't "write out' the entire text at a time, which is why fascinating methods like "think step by step" work at all.
But it can't improve its answer after it has written it, that is a major limitation. When a human writes an article or response or solution, that is likely not the first thing the human thought of, instead they write something down and works on it until it is tight and neat and communicates just what the human wants to communicate. Such answers will be very hard for an LLM to find, instead you mostly get very verbose…
It can be instructed to study its previous answer and find ways to improve it, or to make it more concise, etc, and that is working today. That can easily be automated by LLMs talking to each other.
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#194I agree with Hinton, although a lot hinges on your definition of "understand." I think to best wrap your head around this stuff, you should look to the commonalities of LLM's, image, generators, and even things like Alpha Zero and how it learned to play Go. Alpha Zero is kind of the extreme in terms of not imitating anything that humans have done. It learns to play the game simply by playing itself -- and what they f…
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#195Earlier quoted context omitted.
> One other thing to take into consideration, is that to play the game of Go you can't just think of the next move. You have to think far forward in the game -- even though technically all it's doing is picking the next move, it is doing so using a model that has obviously looked forward more than just one move. It doesn't necessarily have to look ahead. Since Go is a deterministic game there is always a best move (o…
> Since Go is a deterministic game there is always a best move The rules of the game are deterministic, but you may be going a step too far with that claim. Is the game deterministic when your opponent is non-deterministic? Is there an optimal move for any board state given that various opponents have varying strategies? What may be the best move against one opponent may not be the best move against another opponent.
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#196Earlier quoted context omitted.
>I know my world model is fundamentally incomplete. Even more foundationally, I know that there is a world, and when my world model and the world disagree, the world wins. Yeah this isn't really true. There's not how humans work. For a variety of reasons, Plenty stick with their incorrect model despite the world indicating otherwise. In fact, this seems to be normal enough human behaviour. Everyone does it, for somet…
It is a very basic fact that LLMs have no concept of true or false, it only has an ability to look up what text data it has seen before. If you do not understand this you are in no position to discuss LLMs.
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#197I agree with Hinton, although a lot hinges on your definition of "understand." I think to best wrap your head around this stuff, you should look to the commonalities of LLM's, image, generators, and even things like Alpha Zero and how it learned to play Go. Alpha Zero is kind of the extreme in terms of not imitating anything that humans have done. It learns to play the game simply by playing itself -- and what they f…
It's not planning ahead, it is looking at the probabilities of the tokens altogether rather than one by one.
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#198Earlier quoted context omitted.
>I know my world model is fundamentally incomplete. Even more foundationally, I know that there is a world, and when my world model and the world disagree, the world wins. Yeah this isn't really true. There's not how humans work. For a variety of reasons, Plenty stick with their incorrect model despite the world indicating otherwise. In fact, this seems to be normal enough human behaviour. Everyone does it, for somet…
It is a very basic fact that LLMs have no concept of true or false, it only has an ability to look up what text data it has seen before. If you do not understand this you are in no position to discuss LLMs.
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#199Earlier quoted context omitted.
>I know my world model is fundamentally incomplete. Even more foundationally, I know that there is a world, and when my world model and the world disagree, the world wins. Yeah this isn't really true. There's not how humans work. For a variety of reasons, Plenty stick with their incorrect model despite the world indicating otherwise. In fact, this seems to be normal enough human behaviour. Everyone does it, for somet…
It is a very basic fact that LLMs have no concept of true or false, it only has an ability to look up what text data it has seen before. If you do not understand this you are in no position to discuss LLMs.
Re: I disagree with Geoff Hinton regarding "glorified autocomplete"
#200Earlier quoted context omitted.
This doesn't seem like a major difference, since LLMs are also choosing from a probability distribution of tokens for the most likely one, which is why they respond a token at a time. They can't "write out' the entire text at a time, which is why fascinating methods like "think step by step" work at all.
But it can't improve its answer after it has written it, that is a major limitation. When a human writes an article or response or solution, that is likely not the first thing the human thought of, instead they write something down and works on it until it is tight and neat and communicates just what the human wants to communicate. Such answers will be very hard for an LLM to find, instead you mostly get very verbose…