> You have given no argument for why an LLM cannot be intelligent.

I literally did provide a definition and my argument for it already: https://news.ycombinator.com/item?id=47051523

If you want to argue with that definition of intelligence, or argue that LLMs do meet that definition of intelligence, by all means, go ahead[1]! I would have been interested to discuss that. Instead I have to repeat myself over and over restating points I already made because people aren't even reading them.

> Not even that current models are not; you seem to be claiming that they cannot be.

As I have now stated something like three or four times in this thread, my position is that machine intelligence is possible but that LLMs are not an example of it. Perhaps you would know what position you were arguing against if you had fully read my arguments before responding.

[1] I won't be responding any further at this point, though, so you should probably not bother. My patience for people responding without reading has worn thin, and going so far as to assert I have not given an argument for the very first thing I made an argument for is quite enough for me to log off.

> Probabilistic prediction is inherently incompatible with deterministic deduction.

Human brains run on probabilistic processes. If you want to make a definition of intelligence that excludes humans, that's not going to be a very useful definition for the purposes of reasoning or discourse.

> What if 1 + 2 is 2 and 1 + 3 is 3? Then we can reason that under these constraints we just made up, 1 + 4 is 4, without ever having been programmed to consider these rules.

Have you tried this particular test, on any recent LLM? Because they have no problem handling that, and much more complex problems than that. You're going to need a more sophisticated test if you want to distinguish humans and current AI.

I'm not suggesting that we have "solved" intelligence; I am suggesting that there is no inherent property of an LLM that makes them incapable of intelligence.