takedown of OpenAI’s apparent success at ‘Dota 2’https://apple.news/A45CaowNkR7GQ8x92qTIbdg …
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For others following, I expand on it from my point of view in your thread :) tldr - the capabilities needed to produce the existing results would be doable in a traditional ML vision pipeline with human annotation and would still be a win.https://twitter.com/Smerity/status/1031297413388988416 …
I guess I have to ask: what is the question here? Human performance on DOTA doesn’t depend on access to bot buffers or large labeled databases; if we are trying to achieve human level performance with AI, we should try to reach a similar robustness in learning, no?
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It's pure self-play, so no labeled databases, but I think there is real disagreement about how central the role of input representation is to the overall problem. Is learning a complex policy from hand-crafted representations solving 90% of the game, or 10%?
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I was responding to
@smerity’s specific suggestion above of using a traditional pipeline w human labeling to do the vision work that OpenAI abstracted away from - 2 more replies
New conversation -
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