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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”.
Adam Something uploaded a video starting with the definition of intelligence itself, and then explains how something that “acts” intelligent doesn’t mean it “is” intelligent.
I think even “intelligence” here is a stretch. In a very narrow sense, it is intelligent: it creates text, simulates conversations, answers questions. But that is not what intelligence is (and it is all LLMs can do).
“Simulating conversations” to a good enough degree requires intelligence. Why are you drawing a distinction here?
What a silly assertion. Eliza was simulating conversations in the 80s; it was no more intelligent than the current crop of chatbots.
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That’s kind of silly semantics to quibble over. Would you tell a robot hunting you down “you’re only acting intelligent, you’re not actually intelligent!”?
People need to get over themselves as a species. Meat isn’t anything special, it turns out silicon can think too. Not in quite the same way, but it still thinks in ways that are useful to us.