It's just filled to the brim with relations between things. It's good at searching a very large meaning space and create correlations. What it does is to cover great distances and find related things in that large space which needs a long time and large corpus of knowledge to find the connection.

This is not intelligence. It's just a good correlation engine with a very big albeit lossy database of things.

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rnd33 4 hours ago | parent | next [-]

Intelligence is compression, compression requires subtraction, and for some reason LLMs are not good at subtracting. To create a coherent model you kinda have to subtract correlations until only the essential parts are still there.

What I don't understand is why LLMs haven't been able to do this yet, if it's the harness or some orchestration layer above the LLM that is needed. Because fundamentally if you can identify correlations then it's just another small step to prioritize and remove lower value or irrelevant correlations.

I wonder if what's needed is to introduce subtraction tokens in some sense, and in post-training reward the model on that.

	▲	tyromaniac 3 minutes ago \| parent \| next [-]
		I've heard that expression before, but I don't think it can be presented and stated so matter of factly. Where does that put bzip?
	▲	fluoridation an hour ago \| parent \| prev \| next [-]
		Intelligence is compression? What do you mean? Intuitively that doesn't seem right. >What I don't understand is why LLMs haven't been able to do this yet LLMs are just trained on what humans have said. Why is it surprising that it's still not possible to reconstruct the intelligence that wrote all that by working backwards? Think of your own work experience. When you look at a piece of code, say, are you always able to discern why the person did what they did, just from the code, with no additional context?
	▲	jrmg 2 hours ago \| parent \| prev [-]
		Intelligence is compression That’s a controversial statement.

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pyridines 5 hours ago | parent | prev [-]

The very fact that it is able to search within a meaning-space demonstrates that it understands semantics, to some extent. Philosophically, that is profound, for something that is just one big matrix multiplication. Drawing connections between things in meaning-space is surely a facet of intelligence.

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bayindirh 4 hours ago | parent | next [-]

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”.

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pyridines an hour ago | parent | next [-]

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.

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bayindirh an hour ago | parent [-]

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.

	▲	pyridines 27 minutes ago \| parent \| next [-]
		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".)
	▲	hombre_fatal 27 minutes ago \| parent \| prev [-]
		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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