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It seems difficult to argue the additional self knowledge in the second version hasn’t come from its own learning. By my lights, this indicates the program is p
by wruza 3y ago
It seems difficult to argue the additional self knowledge in the second version hasn’t come from its own learning. By my lights, this indicates the program is progressively becoming more self aware.
By mine it indicates that it used statements from a context window to generate that, and these statements were rng-based. A similar thing happens when you upload grey_static_noise.png into the img2img tab and loopback the result for few iterations. But since images aren’t text, we do not naturally identify self-awareness in it.
But at least two questions arise. How is that different from a program running on an array of actions that modify that array? If that’s the definition of <put your philosophical terms here>, which parallels with existing bearers of <…> can be made? (and with that program)
- andywalters 3y agoI don't think the comparison to the image example holds up; while something like a random-ish behavior is at play when it comes to hypothesis generation, the hypothesis evaluation is a different matter. It does seem to reason about its own capabilities intelligently, at least insofar as one can detect coherent reasoning as represented in language. The program you mention using an array might be a thin version of what I've demonstrated here, but it operates on much the same principle. Great question about parallels. I suppose the closest biological parallel would be a human brain reasoning about an external agent's character based on behaviors just observed. (But it quickly falls apart past that: unlike human neuroplasticity, because GPT-4 has no mechanism to update its own weights, knowledge about the agent being evaluated is lost at each new inference unless explicitly included in-context.)