In order to believe this, you'd need to be able to imagine a specific test of something that an LLM could not do under any circumstances. Previously, that test could have been something like "compose a novel sonnet on a topic". Today, it is much less clear that such a test (that won't be rapidly beaten) even exists.

You could use a Markov chain to generate poetry with rhyme and meter[1]. Granted, it wouldn't be a very good one, but that just makes an LLM a refinement to older probabilistic methods.

As for something LLMs are unlikely to do under any circumstances, there's already a fairly obvious example. They can't keep a secret, hence prompt injections.

[1] https://us.pycon.org/2020/schedule/presentation/112/

Do you really believe that an LLM that can keep a secret cannot be made? I suspect that we could do this trivially and the "LLMs can't keep a secret" is a specific product of finetuning for helpfulness.

How about make new scientific discoveries?

A better and better parrot is still a parrot then?

(I’m agreeing with you basically)

Why do you think you are anything more?

Why do you think you're anything more than a pocket calculator?

I don’t.

I think AGI is a questionable concept. We still don't have a good definition of what intelligence really is, and some people keep moving the goal posts. What we need is AI that fills specific needs we have.

If we simply AGI to be "general purpose AI", then my argument is - maybe the approach of LLMs works fine enough for textual generation, but it is not a path towards "general purpose AI".. and what we are going to have is different approaches for different niche use cases.

I'm less convinced there's any unified solution for "general purpose AI" before us here.

And I'm convinced we don't even want "general purpose AI". We want AI for a variety of specific purposes. Admittedly these LLMs are a lot broader than I ever imagined, but they're still limited to generating text. I wouldn't want ChatGPT to drive my car.