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GaryMarcus's profile
Gary Marcus
Gary Marcus
Gary Marcus
@GaryMarcus

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Gary Marcus

@GaryMarcus

CEO/Founder of http://Robust.AI ; cognitive scientist, and best-selling author. New book: http://Rebooting.AI : Building Artificial Intelligence We Can Trust

garymarcus.com
Joined December 2010

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    1. Adam Santoro‏ @santoroAI Aug 20
      • Report Tweet

      "If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis..." I'll never understand this false dichotomy. Not sure how an understanding of the world is built up if not by statistical analysis.

      8 replies 2 retweets 54 likes
      Show this thread
    2. Adam Santoro‏ @santoroAI Aug 20
      • Report Tweet

      This is from the Amazon description of @GaryMarcus new book, though I'm guessing there's a high probability these are not precisely his words. Nonetheless, the same argument pops up in other places too.

      1 reply 0 retweets 3 likes
      Show this thread
    3. Gary Marcus‏ @GaryMarcus Aug 20
      • Report Tweet
      Replying to @santoroAI

      yes. of course the point of writing the book is that argument is too subtle to capture in a jacket description or a tweet.

      1 reply 0 retweets 2 likes
    4. Felix Hill‏ @FelixHill84 Aug 20
      • Report Tweet
      Replying to @GaryMarcus @santoroAI

      It is so subtle I've never quite grasped it. 'Endowing machines with common sense and deep understanding' in the obvious way was tried for 50 years (it's the obvious thing to try first) and didn't work. What's different about your proposal now? (ps. I'll read the book...)

      4 replies 0 retweets 0 likes
    5. Gary Marcus‏ @GaryMarcus Aug 20
      • Report Tweet
      Replying to @FelixHill84 @santoroAI

      Yes, please read the book. But also compare the argument you just made - “it’s already been tried, and failed” — to what might have been applied to deep learning in 2010.

      3 replies 0 retweets 3 likes
    6. Adam Santoro‏ @santoroAI Aug 21
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      Replying to @GaryMarcus @FelixHill84

      From what I've read in recent critiques of DL, the arguments for "more than statistical analyses/pattern recognition" also tend to simply point at what DL can't do (yet). Is there something in your book that *doesn't* point out DL failures, and is different from F+P 1988?

      2 replies 0 retweets 0 likes
    7. Gary Marcus‏ @GaryMarcus Aug 21
      • Report Tweet
      Replying to @santoroAI @FelixHill84

      inter alia, we examine in unprecedented depth what the problems for DL are, focusing on two detailed case studies, AND we also subject *symbolic approaches* to considerable scrutiny, & then make specific proposals about what problems in common sense have highest priority.

      1 reply 0 retweets 2 likes
    8. Murray Shanahan‏ @mpshanahan Aug 21
      • Report Tweet
      Replying to @GaryMarcus @santoroAI @FelixHill84

      Ah - "unprecedented depth". Always works :-)

      1 reply 0 retweets 2 likes
    9. Gary Marcus‏ @GaryMarcus Aug 21
      • Report Tweet
      Replying to @mpshanahan @santoroAI @FelixHill84

      it matters—even in my DL critical appraisal, nothing conveyed the richness of the mismatch between what (pure) deep learning is doing & what actually needs to be done. greatest emphasis in book is on articulating true nature of the problem.

      1 reply 0 retweets 0 likes
    10. Murray Shanahan‏ @mpshanahan Aug 21
      • Report Tweet
      Replying to @GaryMarcus @santoroAI @FelixHill84

      Yes, sure. It was just a joke - because "unprecedented depth" is often the reason the latest DL architecture beats SoTA

      1 reply 0 retweets 1 like
      Gary Marcus‏ @GaryMarcus Aug 21
      • Report Tweet
      Replying to @mpshanahan @santoroAI @FelixHill84

      ha ha!

      7:01 AM - 21 Aug 2019
      1 reply 0 retweets 0 likes
        1. New conversation
        2. Adam Marblestone‏ @AdamMarblestone Aug 21
          • Report Tweet
          Replying to @GaryMarcus @mpshanahan and

          Gary+others, have you considered making a big table that would have rows as research papers or groups thereof and columns as attributes like “pure deep learning”, “hybrid”, “has symbol manipulation”, and so on? Curious what the columns would be for NTM/DNC, say, in your views.

          1 reply 0 retweets 11 likes
        3. Abel.TM‏ @Abel_TorresM Aug 21
          • Report Tweet
          Replying to @AdamMarblestone @GaryMarcus and

          more columns: Unsupervised, Learning from single input, Continuous learning, Open-ended processing, Detects non-solvable scenarios

          0 replies 0 retweets 2 likes
        4. End of conversation

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