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A prevailing sentiment online is that GPT-4 still does not understand what it talks about. We can argue semantics over what “understanding” truly means. I think it’s useful, at least today, to draw the line at whether GPT-4 has succesfully modeled parts of the world. Is it just picking words and connecting them with correct grammar? Or does the token selection actually reflect parts of the physical world?
One of the most remarkable things I’ve heard about GPT-4 comes from an episode of This American Life titled “Greetings, People of Earth”.
LLMs do not think or feel or have internal states. With the same random seed and the same input, GPT4 will generate exactly the same output every time. Its speech is the result of a calculation, not of intelligence or self-direction. So, even if intelligence can be described by an algorithm, LLMs are not that algorithm.
What exactly do you think would happen if you could make an exact duplicate of a human and run it from the same state multiple times? They would generate exactly the same output every time. How could you possibly think differently without turning to human exceptionalism and believing in magic meat?
Maybe, you don’t know that for sure since we are currently far from actually understanding how our brain works. And the amount of external parameters and stimuli required to “run a human from the same state multiple times” dwarfs the input we’re currently feeding LLMs, and would be pretty much impossible to do without technology so advanced it might as well be magic.
For the record, GPT4 specifically is non-deterministic. The current theory is because it uses MoE, but that’s just a theory. Maybe OpenAI knows why. Also, it’s not a random seed, it’s temperature. If you set that to 0, the model should always select the most probable next token because the probability becomes 1 for that token and 0 for all others. GPT3 and most others are basically deterministic at that level, but not GPT4.