The Winograd schema is a language test for intelligent computers. So far, they're not doing well. MORE LANGUAGE FILES: https://www.youtube.com/playlist?list=PL96C35uN7xGLDEnHuhD7CTZES3KXFnwm0 Written with Gretchen McCulloch and Molly Ruhl. Gretchen's podcast Lingthusiasm is at http://lingthusiasm.com/ - and Gretchen's new book, BECAUSE INTERNET, is available: 🇺🇸 US: https://amzn.to/30tLpjT 🇨🇦 CA: https://amzn.to/2JsTYWH 🇬🇧 UK: https://amzn.to/31K8eRD (Those are affiliate links that give a commission to me or Gretchen, depending on country!) REFERENCES: Levesque, H.J., Davis, E., and Morgenstern, L. (2011). The winograd schema challenge. In AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning. Trask, R. (1993). A dictionary of grammatical terms in linguistics. London ; New York: Routledge. (page 233) Winograd, T. (1972). Understanding natural language. Cognitive Psychology, 3(1), 1-191. (page 33) Hunston, S. (2002). Corpora in Applied Linguistics. Cambridge: Cambridge University Press. Jurafsky, D., & Martin, J. (2009). Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition (2nd ed., Prentice Hall series in artificial intelligence). Upper Saddle River, N.J.: Pearson Prentice Hall. Gray, M. & Suri, S. (2019) Ghost work. Boston, M.A.: HMH Books. I'm at https://tomscott.com on Twitter at https://twitter.com/tomscott on Facebook at https://facebook.com/tomscott and on Instagram as tomscottgo
  • roastpotatothiefOP
    2·
    2 years ago

    Since I posted this, Microsoft claims to have built an AI which does have “world knowledge”. It was able to explain how to pile up some objects so they don’t fall. We’ll see though if its claims are true.

    • LvxferreM
      3·
      2 years ago

      I’d take claims from Microsoft with heavy scepticism; they tend to heavily overrate the capabilities of their own software. However, if it is true and accurate, it’s an amazing development, and it might solve problems in the video, like:

      • The trophy doesn’t fit in the bag because it₁ is too big.
      • The trophy doesn’t fit in the bag because it₂ is too small.

      For us humans it’s trivial to disambiguate it₁ as the trophy and it₂ as the bag, because we know stuff like “objects only fit in containers bigger than themselves”. Algorithms usually don’t.