A sufficiently advanced search engine might actually be indistinguishable from intelligence.

After all, until quite recently, chess engines really were quite mechanically search engines too.

I'm just saying you are doing a dis-service to yourself if that is your mental model on how current SOTA models work.

Well, it's "a search engine that applies some transformations on top of the results" doesn't sound to me as a terrible way to think about LLMs.

> can follow logical rules

This is not their strong suite, though. They can only follow through a few levels on their own. This can be improved by agent-style iterations or via invoking external tools.

Let's see how this comment ages why don't we. I've understood where we are going and if you look at my comment history. I have confidence that in 12 months time. One opinion will be proved out with observations and the other will not.

For the "only few levels" claim, I think this one is sort of evident from the way they work. Solving a logical problem can have an arbitrary number of steps, and in a single pass there is only so many connection within a LLM to do some "work".

As mentioned, there are good ways to counter this problem (e.g. writing a plan and then iteratively going over those less-complex ones, or simply using the proper tool for the problem: use e.g. a SAT solver and just "translate" the problem to and from the appropriate format)

Nonetheless, I'm always open to new information/evidence and it will surely improve a lot in a year. As for reference, to date this is my favorite description of LLMs: https://news.ycombinator.com/item?id=46561537