Considering Stallman worked in the MIT AI lab in the era of symbolic AI, and has written GCC (an optimizing compiler is a kind of symbolic reasoner imo), I think he has a deeper understanding of the question than most famous people in tech.
I'm sure while the AI lab folks didn't have the techniques and compute to do ML like we do now, they have thought a lot about the definition of intelligence and what it takes to achieve it, going from the narrow task-specific AIs to truly generic intelligence.
ML/RL allowed us to create systems that given a train/test set, can learn underlying patterns and discover connections in data without a developer having to program it.
Transformers/LLMs are a scaled up version of the approach (I don't want to get into the weeds as it's beside the point)
Stallman asserts LLMs fall short of general intelligence, which I think he has a much better understanding of what that entails than most people give him credit for. Considering his AI past, I'd be surprised if he didn't keep up with the advancements and techniques in the field at least to some degree (or that understanding said techniques would be beyond his ability).
Because of this, I'm running with the theory that he knows what he's talking about even he doesn't elaborate on it here.
In particular the quip that it's really just a "bullshit generator" is 100% correct. But also true for, y'know, all the intelligent humans on the planet.
At the end of the day AI gets stuff wrong, as far as we can tell, for basically the same reasons that we get stuff wrong. We both infer from intuition to make our statements about life, and bolt "reasoning" and "logic" on as after the fact optimizations that need to be trained as skills.
(I'm a lot more sympathetic to the free software angle, btw. The fact that all these models live and grow only within extremely-well-funded private enclosures is for sure going to have some very bad externalities as the technology matures.)
That's not true.
> At the end of the day AI gets stuff wrong, as far as we can tell, for basically the same reasons that we get stuff wrong.
Also not true.
> We both infer from intuition [...]
Also not true.
If you need more information, you can search them or ask an LLM.
Here you go:
https://chatgpt.com/share/69384dce-c688-8000-97f7-23d0628cd5...
He's not comparing them to humans, he attributes knowledge/understanding (enough to pass his bar for "is AI") to yolov5 models, xgboost trained trees and as far as I can tell closed source transformer based models too. But not ChatGPT.