Comment by b40d-48b2-979e
6 hours ago
LLMs aren't people. They don't reason. They're token generators, a black box. Your analogy falls on its face with any scrutiny.
6 hours ago
LLMs aren't people. They don't reason. They're token generators, a black box. Your analogy falls on its face with any scrutiny.
I didn’t claim that LLMs are people or that they reason.
If the behavior of the llm is the same as the behavior of reasonable people then the behavior of the llm is reasonable, regardless of how black of a box they generate tokens out of.
Reasonable people will generate divergent specs for the same prompt. Thus it is reasonable for an LLM to generate divergent specs out of the same prompt.
Edit: I use “reasonable” here in the legal sense of the “reasonable person” standard, not to imply any reasoning process.
[flagged]
Please point to where in my initial comment I indicated that LLMs are human or reason.
If you are unable to do so please withdraw your accusation of gaslighting, a serious form of psychological abuse, and apologize.
it's an analogy, it didnt fall on its face at all. it's just a comparison to highlight the point being made was nonsensical. example: you're just a next action generator controlled by trillions of cells and subconscious dna-based behavior. a black box.
> you're just a next action generator controlled by trillions of cells and subconscious dna-based behavior.
With moral agency and the ability to learn (even if we presume you are correct, which I don't think you are).
moral agency and the ability to learn are implicit in the description you quoted. this isn't some special superpower, all animals have the ability to learn, and many have moral agency. these aren't human specific traits
Reductio ad absurdum.
exactly my point lol
LLMs do reason (they just sometimes don't reason well).
I assure you I've met many devs and "engineers" that reason less than LLMs, and are black boxes, especially in terms of the code they write.
> LLMs do reason
No, they don't.
They are token predictors that use statistical techniques to emit the randomly weighted next most likely token given the previous token list.
The result is a strange mimic of human reasoning, because the tokens it predicts are trained on strings that were produced by humans that were reasoning, but that's not the same thing.
Human cognition is complex and poorly understood, and the nature of the mind is an area of study almost as old as consciousness itself. We don't know exactly how it works, or what its exact relationship to the brain is, but we do know that it is not a simple token predictor.
LLMs, by their very nature are constrained to the concept of language and the relationship between existing words in a corpus. This is a box they can not escape.
Modern neuroscience suggests that the human brain is much more vast than that, and in many ways looks like it is constrained by language, but certainly not limited to it.
They very obviously reason.
it's kind of crazy to think that the transformer architecture can't encode some primitive form of reasoning.