,
5 tweets,
2 min read
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1/ The virtue of PLAY—for humans + machines
~10yrs ago psychologists cheered PLAY for learning, exploring, social bonding, stress management
Humans have cheered PLAY to train machines + AI:
checkers, chess, go, jeopardy, video games
—and now poker...
~10yrs ago psychologists cheered PLAY for learning, exploring, social bonding, stress management
Humans have cheered PLAY to train machines + AI:
checkers, chess, go, jeopardy, video games
—and now poker...
2/ Checkers, chess, go etc are two-person zero-sum games with Nash equilibrium strategies. Many multi-player video games + multi-player poker have more complexity with HIDDEN INFORMATION.
CMU researchers + FB published in Science on training AI to exploit opponent weakness
CMU researchers + FB published in Science on training AI to exploit opponent weakness
3/ Here is description of the goal and technique of “Pluribus” trained on self-play to beat past versions of itself—which is notable because...
4/ The (wise) technique Jeff Bezos advocates in human decision making is “regret minimization”
—most poker AIs also use algorithm of “counterfactual regret minimization”. This one uses a variation that used CPUs instead of GPUS and cost estimated $144 of compute.
—most poker AIs also use algorithm of “counterfactual regret minimization”. This one uses a variation that used CPUs instead of GPUS and cost estimated $144 of compute.
