I never understand the “only a next token predictor” argument. I do share the view that something fundamental about intelligence might be missing in LLMs, but I don’t see how this argument captures anything. If you can predict the exact next word Einstein is about to write, every time, you’re as intelligent as Einstein! It seems very clear that the LLM is also “thinking” about where the output is headed after this next token.

I do hear this position quite a lot though so I’d be interested to hear more about what I might be missing.

It's a statistical machine, so you only predict a statistical Einstein, ie. something that might appear quite like Einstein and even can be fairly accurate in predicting the next word he types, but which is not him, and will be unable to predict the words that are produced not just statistically but with certain intelligence, direction and intuition.

Saying it is a 'next token predictor' should not diminish what LLMs are capable of. It is incredible what can be achieved by a simple rule like this.

Next token predictor is not a very good argument. A submarine does not need to be a fish to swim.

LLMs cannot, by their core design, predict next word correctly every time. That is the main thing you are missing. Another thing is that I know that I am not predicting next word based on othr words in my "trainin data", there is much deeper understanding of most subjects that I am using to "predict next word". This may not be true for everyone, I cannot know for sure, but it might be possible that there are people out there who are just biological LLMs, and in that case I am certain those people will not be able to predict next word Einstein would say either.