"What works for Go may not work for the challenging problems that DeepMind aspires to solve with AI, like cancer and clean energy. IBM learned this the hard way" Picks the only large scale symbolic AI project to illustrate the potential shortcomings of DRL... https://twitter.com/GaryMarcus/status/1161690752524550144 …pic.twitter.com/3lbLcRQ0kz
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I'm sure they did lots of things to make it work. It's still the most symbolic and least DRL system coming out of any modern research lab. It's quite a bit closer to the Gary's cognitive hybrid systems approach than anything out of DeepMind.
hype aside, alphago is a hybrid, with a monte carlo tree sim backbone that traversed trees out of symbol CS 101, alongside the DRL.
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That's an odd argument to make since you also claim DeepMind relies too much on DRL.
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Both can be & are true. Really telling to me is that DRL on its own worked for Atari games but not Go— and that DM’s spin on Go really downplayed the hybrid aspect that was essential to its success. (It was also apparently necessary to build in the rules for Go, unlike Atari.)
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