Comment by bayindirh
7 hours ago
It’s not intelligence if you are the one who gives the correlations to the model in the pre-training. It’s Word2Vec, applied. Model doesn’t learn anything. You embed these correlations and build it from there. It just searches the space.
As my AI professor said in the first lecture: “All AI is advanced search”.
Okay, I guess you're right that its ability to do this is just correlational, which doesn't imply it has any understanding. However, you have to conclude that some tasks which we used to believe required intelligence don't actually require any, which is disconcerting.
No, what I would say is the tasks which are handled in a passable manner by LLMs can be mathematically modeled with some reasonable accuracy.
Many things are predicted by models in our planet. From weather to production and material science. Building the model needs intelligence, running the model does not.
The person who came up with the formulae for CFD was intelligent. The computer running the model is not. Same for LLMs, chess engines, engine ECUs and financial prediction systems.
Again, for the example’s sake; the person who came up with an algorithm is intelligent. The model mixing its training data to emit something similar is not.
This starts to feel like you're defining the word intelligence out of any meaning and out of any way we apply that word.
So when LLMs can do all human knowledge work, and do it better than humans, we'll be in the mines listening to you go on about how it's actually just autocomplete or just math, a distinction that apparently means nothing.
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I get what you're saying. The thing itself is just math. I'll just say it depends on how you define intelligence. If at some point we're be able to simulate a human brain with 100% accuracy, I would say that it is intelligent, it sounds like you would not. (I don't mean to imply consciousness or personhood or anything else by "intelligent".)
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