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AdamMarblestone's profile
Adam Marblestone
Adam Marblestone
Adam Marblestone
@AdamMarblestone

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Adam Marblestone

@AdamMarblestone

Technologist, Scientist

adammarblestone.org
Joined February 2009

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    1. Joscha Bach‏ @Plinz 12 Nov 2019
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      Replying to @rutumulkar @GaryMarcus

      While the transformer is an important contribution to ML (and the implied idea of maintaining identity via attention imho relevant to AGI), GPT-2 is a text prediction tool, not an AGI architecture. The quality of a chatbot built on GPT-2 is unrelated to how close we are to AGI.

      3 replies 0 retweets 9 likes
    2. Gary Marcus‏ @GaryMarcus 12 Nov 2019
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      Replying to @Plinz @rutumulkar

      that’s retrenchment and revisionist history. few months ago people were perfectly happy to talk about gpt-2 as an understanding tool; it’s in the original paper, the title of the Bet paper, sutskekers quote to the New Yorker, etc. i have posted about this before.

      2 replies 0 retweets 1 like
    3. Joscha Bach‏ @Plinz 12 Nov 2019
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      Replying to @GaryMarcus @rutumulkar

      I don't find this claim in the GPT-2 paper, and have not met any serious researcher who claimed that GPT-2 is able to understand text in any real sense. The NLU community may use the word "understanding" more broadly than it should, but is very aware of the limitations.

      3 replies 1 retweet 1 like
    4. Gary Marcus‏ @GaryMarcus 12 Nov 2019
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      Replying to @Plinz @rutumulkar

      Did anyone in deep learning community call Sutskever out for equating understanding and prediction in the New Yorker? for pitching GPT-2 in orig. blog as having "rudimentary reading comprehension? Or BERT paper for having "understanding" in title? AFAIK, no.

      1 reply 0 retweets 1 like
    5. Adam Marblestone‏ @AdamMarblestone 12 Nov 2019
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      Replying to @GaryMarcus @Plinz @rutumulkar

      On the one hand, “understanding” and pure NLP papers shouldn’t be in same sentence/article. On the other, lack thereof in pure NLP has ~0 to do with how close we are to AGI. In right grounded lifelong causal environment, prediction may (or may not) be key driver of understanding.

      1 reply 0 retweets 1 like
    6. Rutu Mulkar‏ @rutumulkar 12 Nov 2019
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      Replying to @AdamMarblestone @GaryMarcus @Plinz

      That is a ridiculous statement. NLP -> Information Extraction -> Knowledge graphs -> causal reasoning. It is all connected. maybe we have different definitions of NLP?

      1 reply 0 retweets 1 like
    7. Adam Marblestone‏ @AdamMarblestone 12 Nov 2019
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      Replying to @rutumulkar @GaryMarcus @Plinz

      That reasonable opinions and definitions could differ on such a subject is quite expected and ok to me.

      2 replies 0 retweets 0 likes
    8. Gary Marcus‏ @GaryMarcus 12 Nov 2019
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      Replying to @AdamMarblestone @rutumulkar @Plinz

      hmm. i think AGI without NLU is logically possible but extremely unlikely, and that real progress towards NLU would show up on the kind of dynamic understanding benchmark i am trying to develop

      1 reply 0 retweets 0 likes
    9. Adam Marblestone‏ @AdamMarblestone 12 Nov 2019
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      Replying to @GaryMarcus @rutumulkar @Plinz

      Is the language “grounded” in your benchmark? Or just text->text? I don’t see getting far in a pure text universe.

      1 reply 0 retweets 0 likes
    10. Gary Marcus‏ @GaryMarcus 12 Nov 2019
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      Replying to @AdamMarblestone @rutumulkar @Plinz

      as i noted yesterday @Wolfram_Alpha occasionally does fine in such circumstances i think a strong an innate kernel plus wikipedia could take the right algorithm a long way, much further than any current system

      1 reply 0 retweets 0 likes
      Adam Marblestone‏ @AdamMarblestone 12 Nov 2019
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      Replying to @GaryMarcus @rutumulkar and

      Sounds interesting!

      5:14 PM - 12 Nov 2019
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      0 replies 0 retweets 1 like

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