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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. Grady Booch‏Verified account @Grady_Booch 24 Nov 2018
      • Report Tweet
      Replying to @IntuitMachine

      Again, you have changed the subject. Most of this money is currently not being applied to general A.I. but to DL only.

      1 reply 0 retweets 2 likes
    2. Carlos E. Perez  🧢‏ @IntuitMachine 24 Nov 2018
      • Report Tweet
      Replying to @Grady_Booch

      I don't think you can make that conclusion that the money is being spent on DL only. I don't know yet where the Chinese, Canadians, French, Germans are placing bets. DoD have some ideas, which they call 'Third Wave AI', that goes beyond symbolists and connectionist approaches.

      1 reply 0 retweets 0 likes
    3. Grady Booch‏Verified account @Grady_Booch 24 Nov 2018
      • Report Tweet
      Replying to @IntuitMachine

      I am very familiar with DARPA’s program. Yes, it desires to push beyond DL, but DL is very much the baseline. As for China - and it is difficult to get uncensored information- they seem to have a maniacal DL focus.

      3 replies 0 retweets 2 likes
    4. Grady Booch‏Verified account @Grady_Booch 24 Nov 2018
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      Replying to @Grady_Booch @IntuitMachine

      But this conversation is distracting: my simple original point is that there is a huge pile of money at national levels being poured into some very specific A.I. approaches...and that is a little concerning to me, not unlike what happened in Japan.

      1 reply 1 retweet 4 likes
    5. Grady Booch‏Verified account @Grady_Booch 24 Nov 2018
      • Report Tweet
      Replying to @Grady_Booch @IntuitMachine

      You went off on a tangent suggesting I condemned general funding for research..that is not at all what I was saying. Don’t overthink the topic: my spidey sense is tingling, that is all.

      1 reply 0 retweets 0 likes
    6. Carlos E. Perez  🧢‏ @IntuitMachine 24 Nov 2018
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      Replying to @Grady_Booch

      If your concern is that there's going to be a lot of wasted money then I think that is misplaced. I guarantee that many of these nations will 'waste' a ton of money for minimal results. That's just the nature of basic research.

      1 reply 0 retweets 0 likes
    7. Grady Booch‏Verified account @Grady_Booch 24 Nov 2018
      • Report Tweet
      Replying to @IntuitMachine

      No, I am mostly concerned of the opportunity cost...as @GaryMarcus has observed, a lot of these new and heavily funded efforts are proceeding with vigor but with hardly any understanding or appreciation for the history of AI

      2 replies 2 retweets 10 likes
    8. Thomas G. Dietterich‏ @tdietterich 24 Nov 2018
      • Report Tweet
      Replying to @Grady_Booch @GaryMarcus @IntuitMachine

      What great success of AI history are people forgetting? The high development cost and higher ownership cost of hand-coded knowledge bases?

      5 replies 1 retweet 3 likes
    9. Gary Marcus‏ @GaryMarcus 24 Nov 2018
      • Report Tweet
      Replying to @tdietterich @Grady_Booch @IntuitMachine

      Google Search was built on classical AI and hand-coded knowledge bases. Not too shabby. So was Siri AFAIK, though embeddings surely play a role now. Weather-prediction is still classical models, not deep learning. Best driving systems still hybrids, as far as I know.

      5 replies 0 retweets 7 likes
    10. David Pfau‏ @pfau 24 Nov 2018
      • Report Tweet
      Replying to @GaryMarcus @tdietterich and

      PageRank was definitely not "classical AI" or a hand-coded knowledge base. This is patently ridiculous. Knowledge Graph came much much later.

      4 replies 0 retweets 4 likes
      Gary Marcus‏ @GaryMarcus 24 Nov 2018
      • Report Tweet
      Replying to @pfau @tdietterich and

      i wasn’t talking about knowledge graph; lots of hand coded stuff in Google Search as a whole, from what I understand. & pagerank itself does recursive link counting etc; easy to implement with Lisp, not so easy w a neural net. only much later did neural nets get added, afaik

      5:16 PM - 24 Nov 2018
      • 1 Like
      • Bharadwaaj
      2 replies 0 retweets 1 like
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        2. David Pfau‏ @pfau 24 Nov 2018
          • Report Tweet
          Replying to @GaryMarcus @tdietterich and

          It's certainly not deep learning either, that popped up at Google around the same time as Knowledge Graph. PageRank is (roughly) computing the top eigenvector of an adjacency graph matrix. I wouldn't call that deep learning *or* classical AI.

          2 replies 0 retweets 3 likes
        3. Gary Marcus‏ @GaryMarcus 24 Nov 2018
          • Report Tweet
          Replying to @pfau @tdietterich and

          i said search, not just pagerank (which is a component). Google has or had large teams of folks hand writing templates for various special cases, as I understand it.

          2 replies 0 retweets 0 likes
        4. 2 more replies
        1. Dave Moore‏ @davmre 24 Nov 2018
          • Report Tweet
          Replying to @GaryMarcus @pfau and

          PageRank is essentially matrix decomposition - easy to implement with SGD and in some sense actually *the* fundamental operation of deep learning.

          0 replies 0 retweets 1 like
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