• melsaskca@lemmy.ca
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    18 days ago

    But humans can jump to conclusions that AI would never “think” of.

    • baines@lemmy.cafe
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      18 days ago

      actually recentish chess bots showed playing in a uniquely bot sort of way by sacking points for long term position control well past current human norms was a viable strat

      google ‘deep positional sacrifice used as a tool for total restriction’ for videos on it

      so if anything it’s reverse

      chess isn’t solved but it is deterministic not some purely subjective creative art

      why would a human be better at it?

      • melsaskca@lemmy.ca
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        18 days ago

        Theoretically the humans would win one every so often because sometimes humans “zig” when AI can only “zag”? It’s like scientific calculators doing math way more quickly than any human on earth, but they are not necessarily better at it. I don’t know, it’s a brave new world and you may be right.

        • baines@lemmy.cafe
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          17 days ago

          yea nah

          it being a deterministic game means there is a right answer or correct play at each point

          now we obviously realized our foundational principles are wrong at times, otherwise this new computer method would not have been shocking but that was a human failing and not something you could exploit against a bot

          the kind of leap you are envisioning is something that would only really work in a chaotic system

          the idea being there that human can leap to a right conclusion not completely supported by facts

          you could arguably just call that gambling

          • tquid@sh.itjust.works
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            16 days ago

            I wouldn’t call it a “leap” but a few years ago some researchers did find a weird byway in the then-current go-playing "AI"s (neural-network setups, as someone else pointed out). They had to cheat a bit by examining the NN’s “thinking” more directly, and found a cyclic strategy that allowed a human to beat the machine.

            https://www.far.ai/blog/even-superhuman-go-ais-have-surprising-failure-modes

            It’s interesting for more “AI”-type stuff generally. The point is not so much “us with our special brains will always find ways to defeat AI” but more “there are odd blind spots that you would not predict by just looking at the output/games, and these can be exploited with appropriate technology.”

            Edit: remove redundantly redundant redundancy

            • baines@lemmy.cafe
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              17 days ago

              that is cool and not uncommon in algos in general

              bad cost function, poor fit / overfit, local inflection etc