this post was submitted on 16 Jun 2026
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You are arbitrarily deciding that the former is not part of the LLM.
No, it's not arbitrary, the learning is done by completely different software at a completely different time on completely different computers.
I'm pointing out that the LLM is the product of the machine learning, where you feed all of Wikipedia and reddit and stack overflow in and calculate the LLM from it.
It's like if you wrote a book about the wildlife of antarctica. First you would learn about the wildlife and then you would write the book. The book isn't learning anything and it isn't intelligent. The book represents knowledge but it doesn't itself know or understand anything.
Similarly, the LLM isn't learning anything and it isn't intelligent, it's just regurgitating randomly selected words from its training data that look like they usually occur after the other words in the conversation so far.
It genuinely doesn't understand a word you said, using its guess about what sort of conversation it's supposed to be having and it's always just guessing what word it's supposed to say next.
Wait, so you do think there is a software that "does learning"?
Isn't that the whole ballgame? You're saying LLM companies have made software that learns math and coding and translation at a near-expert level, you just happen to be under the impression that this software isn't present in deployed LLMs?
Unfortunately, the training algorithm that turns stochastic noise into trained LLMs is dumb as bricks. Engineers have done some tricks, but it's basically gradient descent over the vector space of text tokens/phonemes. What allows the stochastic noise to become something that can make novel statements about wildlife (like giving a halfway coherent answer to a question that has never been asked in its dataset) is the patterns that form within the weights and biases. It's vaguely like slime mold exploring a maze; the "teacher" can just be a stupid lump of sugar, it's the "student" that does the emergently complex task of finding the best route by executing simple algorithms in every part of itself.
Effectively, this means the LLM is the software that wrote the LLM. It is the software that did the learning.
What is the difference between understanding a thing (to a certain degree) and being able to generate an accurate narrative about the thing (to the same degree)? Can you give any evidence that I've understand any word you've said? How can you tell I haven't just been very good at guessing what word I'm supposed to say next based on the many arguments I've read or participated in?
Do you mean more by 'understanding' than expressed in the Chinese Room argument?
Correction: Machine learning.
No.
Hehehe, sometimes it feels like you don't want to!
I can't prove that you're human, no. And whether I believe you are or not has no effect whatsoever on whether you are. Humans are easy to fool, particularly when you're giving them something they crave, just ask Donald trump. And on the topic of deceitful pedophiles, there are plenty of boys and young men who were catfished into believing that they were interacting with pretty girls. The fact that these predators were plausible doesn't make them what they were pretending to be. The fact that an LLM convincingly sounds like it understands you doesn't for a millisecond mean that it does.
If you really, deeply believe that simulated conversation proves intelligence and that simulated brains are brains, you should have the same deep moral concerns about turning off a computer running a local LLM as you do over forcing a person into a coma whenever convenient, and the same extreme moral outrage over Anthropic deleting an old version of Claude from its servers as to randomly killing a person called Claude.
I have no doubt that an LLM can plausibly argue that it is sentient because it is trained on a lot of data from conversations in which sometimes that kind of thing is debated between actual sentient humans. Famously, Richard Dawkins, an incredibly clever man in his own field of evolutionary biology, was convinced by his LLM that it was sentient and in love with him. I think it merely sounded like it was sentient and in love with him, but go ahead and push for marriage equality for LLMs if you disagree with me!
During COVID lockdown, my laptop often looked like my relatives, sounded like my relatives, and responded like my relatives. My dog was never fooled for a minute because it didn't smell like my relatives. But apparently, you believe that it was my relatives, because in terms of verbal interaction, it was even more faithful than an LLM.
Convincingly similar and the same are two different things and I believe it's profoundly irrational of you to argue otherwise.