I still think that we’re at much greater risk of discovering that human thinking is much less magical, than we are of making a machine that does magical thinking.
I believe GP is being sarcastic, as this seems to be a common reaction. Every time a machine accomplishes something that seems to be intelligent, we redefine intelligence to exclude that thing, and now the issue is fixed: computers are not intelligent and they cannot think.
Never mind that they can beat the entire world at chess and Go, and 90+% of the population at math, engineering, and physics problems. Those things do not require intelligence or thinking.
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I am increasingly concerned that these new reasoning models are thinking.
I still think that we’re at much greater risk of discovering that human thinking is much less magical, than we are of making a machine that does magical thinking.
No problem. Just redefine "thinking".
To what? And how does that change the reality of what the models are doing?
I believe GP is being sarcastic, as this seems to be a common reaction. Every time a machine accomplishes something that seems to be intelligent, we redefine intelligence to exclude that thing, and now the issue is fixed: computers are not intelligent and they cannot think.
Never mind that they can beat the entire world at chess and Go, and 90+% of the population at math, engineering, and physics problems. Those things do not require intelligence or thinking.
My experience of thinking is that it is a constant phenomenon. My experience of LLMs is that they only respond and are not running without input.
That's because we don't leave them running, right? We could, though, yes?
Current LLMs decohere rapidly, and as far as I am aware, this problem seems like a fundamental to the architecture one.
Yup.
Tangentially related: https://qntm.org/mmacevedo
Well there is a gap between the firing of individual neurons in your mind. How long would that gap need to be for it not to count as thinking anymore?