Brain behaviour is a big influence and inspiration on how machine learning techniques are designed.
I repeat, the LLM is not doing machine learning while users are using it.
This isn’t to say LLMs are trustworthy or reliable. They are not.
We agree here.
More that humans think much more highly of themselves than is really warranted.
And we agree here too, but to trust an LLM to tell you the truth on your question that you don't know the answer is like trusting some random drunk at the pub, because you don't know whether the answer is from an LLM hallucination, a random lie/error on reddit or an expert's contribution to wikipedia.
And to trust an LLM when there's a trained programmer or professional journalist is stupid. Sure, an LLM might even sometimes write as good or better code than an intern, but again, the LLM is not learning from its mistakes as you correct it. The intern gradually becomes an expert. The LLM does not. Paying interns is an investment in future programmers, who get more expensive the more experienced they are.
The LLM is currently cheaper than the intern, but LLM pricing needs to go up by a factor of about ten to cover running costs let alone pay off the vastly more immense debts of buying all that hardware.
Sleep is generally understood physiologically to be required to formulate long term memory (eg. as described in this paper).
Like I said before, humans sleep every night, with rare exceptions. LLMs do not get retrained every night. The human brain adapts to feedback loops during everyday interactions, not just overnight. It's a silly analogy and this is a silly point to defend.
There are plenty of textbooks that say that volatile running RAM is like short term memory and hard disks and SSDs are like long term memory, but it would be silly to reverse the analogy as you are doing and claim that sleep is pressing the save button on the day's learning, or that this makes your word processor the same as your human intelligence because, and this is the central point you've been trying to argue around and about and against, they're doing fundamentally different things, and telling me one was inspired by the other doesn't change that. An LLM is fundamentally a stochastic regurgitator whose training is designed primarily to make it sound right. A human brain just doesn't work that way.
If you truly believe that the LLM is learning like a human or intelligent like a human, you are confusing analogies for reality.