A pic from Marvin Minsky's 1991 paper: Logical vs Analogical or Symbolic vs Connectionist or Neat vs Scruffy. The pic summarizes what's going on and what should be done!pic.twitter.com/WnsCNhWZxU
The debate continues! Friends and foes of #Deeplearning and #AI: how strong were the replies to my recent appraisal of deep learning? @Medium, comment section is open.
Please RT to help advance the discussion 
https://medium.com/@GaryMarcus/in-defense-of-skepticism-about-deep-learning-6e8bfd5ae0f1?source=twitterShare-d7e74ac84d28-1515934338 …
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Assuming that the purpose of Deep Learning is to replicate general intelligence ("human like") is perhaps too much to assume. But ok, business is business!
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This debate has completely gotten off the rails. There's really no coherence here, furthermore a majority of the audience simply doesn't understand the subtleties of the subject matter. LeCun was right when he dismissed it by just saying its all wrong without explanation.
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It actually passes through four stages. First it is ignored.
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NN have a long history of hype -- and success as well. But we should learn from overhyped claims. (credits to
@lm101talk)pic.twitter.com/nskOay9zGW
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btw regarding the reverse function example, symbolic AI has been able to correctly discover the definition for like 10-20 years ¯\_(ツ)_/¯
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and not just a finite approximation either. the full definition that works for every length list
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On skepticism, I'm a bit skeptical on any constructive outcome of the discussion. IMHO we need more code, datasets, benchmarks, results, metrics, science,…https://twitter.com/omerlevy_/status/951945601838563328 …
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