Who said anything about matching human intelligence though? If that's the reference point, then nothing in the field of AI has ever had the 'right' to be called that. Computer vision, ML-based optimization of anything or ranking/recommendation systems are all considered to be within AI, despite none of them being remotely similar to 'human intelligence'.

This is the main point of my post - I feel like people retroactively try to see AI as being some kind of an endorsement term, or having to do anything regarding humans - or that 'intelligence' is in itself an endorsement and something so extremely good that only humans can be bestowed with it. In reality, these comparisons only appeared after the boom of generative AI and would've been seen as ludicrous by any AI researchers prior to it.

Yes, I agree that the rise of gAI has had a major impact on this, but the fact that the meaning of AI in CS and AI in sci-fi are different was also very apparent before all this happened. Marketing and finance people have been trying to associate the hard-math, grounded-in-reality AI with "it's magical, it's smart like a human!" many times before, this time they just were very successful at it.

The idea that LLMs just repeat their training data is just wrong. It’s easy to test them and prove this is not the case. In some situations they may do that, typically when they don’t have much data on some topic. But in many other cases, it’s easy to verify that they are able to synthesize new output that is not simply a repetition of their training data.

Software development is a great example, which also illustrates the ability of LLMs to reason (whether you want to call it e.g. “simulating reasoning” doesn’t matter - the results are what counts.) They can design new programs, write new code, debug code they’ve never seen before, and explain code they’ve never seen before. None of that would be possible if they were simply repeating their training data.

The reason why I said it sounded that way to me is that the 'intelligence' part in AI was never meant to imply some kind of superhuman ability. I highlighted the age of the field to point out precisely that judging any AI systems as humans would've been seen as outlandish and laughable for most of the field's existence. If computer vision is AI, then surely text generators can also be. It doesn't have to be a glamorous term, it's just the technical field.

Besides, if LLMs only recycled training data with no changes, they'd just be really bad search engines. Generative AI was created initially to improve training, not for human consumption - the fact that it did improve training shows that the result is greater than the sum of its parts. And since nowadays they're good enough to pass for conversation, you can even observe that on your own by asking a question that doesn't appear anywhere on the training dataset - if there's enough coverage on that topic otherwise, I've seen them give very reasonable answers.