When humans fail a task, it’s obvious there is no actual intelligence nor understanding.

Intelligence is not as cool as you think it is.

Depends how precisely you define novel - I don't think LLMs are yet capable of posing and solving interesting problems, but they have been used to address known problems, and in doing so have contributed novel work. Examples include Erdos Problem #728[0] (Terence Tao said it was solved "more or less autonomously" by an LLM), IMO problems (Deepmind, OpenAI and Huang 2025), GPT-5.2 Pro contributing a conjecture in particle physics[1], systems like AlphaEvolve leveraging LLMs + evolutionary algorithms to generate new, faster algorithms for certain problems[2].

[0] https://mathstodon.xyz/@tao/115855840223258103

[1] https://huggingface.co/blog/dlouapre/gpt-single-minus-gluons

[2] https://deepmind.google/blog/alphaevolve-a-gemini-powered-co...

None of my codebases are in their training data, yet they routinely contribute to them in meaningful ways. They write code that I'm happy with that improves the codebases I work in.

Do you not consider that novel problem solving?

Phrases like "actual understanding", "true intelligence" etc. are not conducive to productive discussion unless you take the trouble to define what you mean by them (which ~nobody ever does). They're highly ambiguous and it's never clear what specific claims they do or don't imply when used by any given person.

But I think this specific claim is clearly wrong, if taken at face value:

> They just regurgitate text compressed in their memory

They're clearly capable of producing novel utterances, so they can't just be doing that. (Unless we're dealing with a very loose definition of "regurgitate", in which case it's probably best to use a different word if we want to understand each other.)

The fact that the outputs are probabilities is not important. What is important is how that output is computed.

You could imagine that it is possible to learn certain algorithms/ heuristics that "intelligence" is comprised of. No matter what you output. Training for optimal compression of tasks /taking actions -> could lead to intelligence being the best solution.

This is far from a formal argument but so is the stubborn reiteration off "it's just probabilities" or "it's just compression". Because this "just" thing is getting more an more capable of solving tasks that are surely not in the training data exactly like this.