As someone who is not nearly as impressed with AI as you, thank you for the Turing test link. I've personally been convinced that LLMs were very far away from passing it, but I realize I misunderstood the nature of the test. It depends way too heavily on the motivation level of the participants. That level of "undergrad small-talk chat" requires only slightly more than Markov-chain level aptitude. In terms of being a satisfying final showdown of human vs AI intelligence, DeepBlue or AlphaGo that was not.
I still hold that we're very far away from AI being able to pass a motivated Turing test. For example, if you offered me and another participant a million dollars to win one, I'm confident the AI would lose every time. But then, I would not be pulling any punches in terms of trying to hit guardrails, adversarial inputs, long-context weaknesses etc. I'm not sure how much that matters, since I'm not sure whether Turing originally wanted the test to be that hard. I can easily imagine a future where AI has Culture-level intelligence yet could still not pass that test, simply because it's too smart to fully pass for a human.
As for the rest of your post, I'm still not convinced. The problem is that the model is "demonstrating intelligence" in areas where you're not qualified to evaluate it, and thus very subject to bullshitting, which models are very competent at. I suspect the Turing test wins might even slowly reverse over time as people become more exposed to LLMs. In the same way that 90s CGI now sticks out like a sore thumb, I'll bet that current day LLM output is going to be glaring in the future. Which makes it quite risky to publish LLM text as your own now, even if you think it totally passes to your eyes. I personally make sure to avoid it, even when I use LLMs privately.
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As someone who is not nearly as impressed with AI as you, thank you for the Turing test link. I've personally been convinced that LLMs were very far away from passing it, but I realize I misunderstood the nature of the test. It depends way too heavily on the motivation level of the participants. That level of "undergrad small-talk chat" requires only slightly more than Markov-chain level aptitude. In terms of being a satisfying final showdown of human vs AI intelligence, DeepBlue or AlphaGo that was not.
I still hold that we're very far away from AI being able to pass a motivated Turing test. For example, if you offered me and another participant a million dollars to win one, I'm confident the AI would lose every time. But then, I would not be pulling any punches in terms of trying to hit guardrails, adversarial inputs, long-context weaknesses etc. I'm not sure how much that matters, since I'm not sure whether Turing originally wanted the test to be that hard. I can easily imagine a future where AI has Culture-level intelligence yet could still not pass that test, simply because it's too smart to fully pass for a human.
As for the rest of your post, I'm still not convinced. The problem is that the model is "demonstrating intelligence" in areas where you're not qualified to evaluate it, and thus very subject to bullshitting, which models are very competent at. I suspect the Turing test wins might even slowly reverse over time as people become more exposed to LLMs. In the same way that 90s CGI now sticks out like a sore thumb, I'll bet that current day LLM output is going to be glaring in the future. Which makes it quite risky to publish LLM text as your own now, even if you think it totally passes to your eyes. I personally make sure to avoid it, even when I use LLMs privately.
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