You can’t just give OpenAI a mulligan on vision, if you want to claim superhuman performance. Not saying there is zero progess here but on the question of inducing a game from experience, and beating humans on a level playing field, it’s a step back compared to DQN on Atari.https://twitter.com/Smerity/status/1031248288958177280 …
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There are caveats ofc., but OpenAI has been transparent about the compute & simplifications they used. Focusing on a subset of a problem at first is one of the basic principles of AI research, so it's hardly fair to single them out for an 'would have been more impressed' attitude
Surely I didn’t single them out. I wrote a whole arXiv on AlphaGo, in January...
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Fair enough, bad wording on my part. I just meant that sample efficiency is clearly an open problem to be addressed, yes, but the accomplishment here should still be recognized. I also wrote a whole article on this after all and tend to agreehttps://thegradient.pub/why-rl-is-flawed/ …
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