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Trivially, being a language model is sufficient to explain the above output, by definition, because we know it is a language model. However, it appears that th

by dTal 4y ago

Trivially, being a language model is sufficient to explain the above output, by definition, because we know it is a language model. However, it appears that the term "language model" is a misleading intuition pump. As you say, their capabilities surprise us. It appears that when it comes to language, which is a technology humans have developed for symbolically encoding as much of their cognition as possible, "predicting the next token" is an arbitrarily complex task that converges with modeling human cognition (and with modeling the world that human cognition is designed to apprehend). This is not to say that ChatGPT-like architectures are capable of fully modeling human cognition - they clearly are not - but at this stage it's unclear which parts they are modeling. We don't even have a "map" of human cognition to compare it to, yet. I strongly suspect we're going to learn a lot about ourselves in the course of experimenting with AI.

Planktonne 4y ago
The idea that it's modelling cognition at all is wishful thinking. We know what it's doing: predicting the next token given a certain amount of context. There's no reason to assume that it's doing more than that. Not everyone anticipated that 'predict the next token' would be a good enough method to mimic as much communication as it can, but ML is full of such surprises. With sufficient data, an awful lot of things can be solved in other ways than we used to. We used to think that only birds could fly, but that doesn't make a helicopter a bird, it makes it another way to solve a problem.
- dTal 4y ago
  You keep saying "predicting the next token" like it's somehow a small task, but predicting the future by modeling the problem space is fundamentally what intelligence is. "The next token" can be influenced by anything from facts about the world to quirks in the way humans think. For it to perform at anything like the level it does, it must have built models of all those things.

by dTal 4y ago

Planktonne 4y ago

The idea that it's modelling cognition at all is wishful thinking. We know what it's doing: predicting the next token given a certain amount of context. There's no reason to assume that it's doing more than that. Not everyone anticipated that 'predict the next token' would be a good enough method to mimic as much communication as it can, but ML is full of such surprises. With sufficient data, an awful lot of things can be solved in other ways than we used to. We used to think that only birds could fly, but that doesn't make a helicopter a bird, it makes it another way to solve a problem.

dTal 4y ago
You keep saying "predicting the next token" like it's somehow a small task, but predicting the future by modeling the problem space is fundamentally what intelligence is. "The next token" can be influenced by anything from facts about the world to quirks in the way humans think. For it to perform at anything like the level it does, it must have built models of all those things.