> Forcing it to be concise doesn't work because it wasn't trained on token strings that short.
replyThis is a 2023-era comment and is incorrect.
Anything I can read that would settle the debate?
replyLLMs architectures have not changed at all since 2023.
reply> but mmuh latest SOTA from CloudCorp (c)!
You don't know how these things work and all you have to go on is marketing copy.
Yea you don't know anything about LLM architectures. They often change with each model release.
replyYou also aren't aware that there's more to it than "LLM architecture". And you're rather confident despite your lack of knowledge.
You're like the old LLMs before ChatGPT was released that were kinda neat, but usually wrong and overconfident about it.
They’re able to solve complex, unstructured problems independently. They can express themselves in every major human language fluently. Sure, they don’t actually have a brain like we do, but they emulate it pretty well. What’s your definition of thinking?
replyWhen OP wrote about LLMs "thinking" he implied that they have an internal conceptual self-reflecting state. Which they don't, they *are* merely next token predicting statistical machines.
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