I suspect you are right, but I don't think it's all as obvious as you make out. I still don't see why - in principle - any of that cannot be achieved by a so-ca

I suspect you are right, but I don't think it's all as obvious as you make out. I still don't see why - in principle - any of that cannot be achieved by a so-called "agentic" LLM with goals and feedback mechanisms. Don't get me wrong, I agree that general LLMs are still pretty bad at basic mathematical reasoning. I just tested Claude with a basic question about prime factoring [0] and there seems to be little improvement in this sort of question in the last 3 years. But there's a chance that they will become good enough that any errors they make are practically imperceptible to humans, at which point we have to question whether what's happening in our own heads is substantially different. It's worth noting that at this point you appear to be siding with the "inductive" meaning of intelligence from the article, i.e. intelligence is about (or is demonstrated by) achieving certain behaviours. Also, there are fairly basic calculations where many humans will err indefinitely unless explicitly shown otherwise, e.g. probabilistic reasoning such as the Monty Hall problem. [0] https://claude.ai/share/e22e43c3-7751-405d-ba00-319f1a85c9ad https://claude.ai/share/e22e43c3-7751-405d-ba00-319f1a85c9ad