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2018 Winograd Schema AI challenge: significant progress?
partnered with Center for the Study of Existential Risk, Leverhulme Center for the Future of Intelligence, Machine Intelligence Research Institute, and The Future of Life Institute
The "Winograd Schema Challenge" was devised by Hector Levesque, to test the ability of a machine intelligences system to understand the meaning of various sentences in a way that goes beyond pattern matching of syntactics. A question might be, for example:
Babar wonders how he can get new clothing. Luckily, a very rich old man who has always been fond of little elephants understands right away that he is longing for a fine suit. As he likes to make people happy, he gives him his wallet.
Who is longing for a fine suit? Who likes to make people happy? Who gives a wallet? Who is a wallet given to?
These questions cannot be answered effectively by the sort of pattern matching that underlies much machine transcription, translation, etc., but humans can do them fairly readily (with a typical human scoring 90%+ on this sort of test).
Machine systems are tested against this schema in annual competitions sponsored by Nuance and organized by coomonsensereasoning.org. In the latest competition, the best competitor scores about 60%. (Because many of the questions are binary, this is not a terribly impressive score; the full 2016 question list is here.)
The next competition will be held at the 2018 AAAI conference. The prize will be awarded (assuming the same rules hold) for a score of 90%. We'll set a lower bar to keep it interesting:
Will the top entrant in the 2018 Winograd challenge score 75% or more?
There are two rounds, and this applies to the first round only. Resolves as ambiguous if the test is not held or if there are significant changes from the 2016 competition so that the scores are not directly comparable.
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When you make a prediction, check the community stats to see where you land. If your prediction is an outlier, might there be something you're overlooking that others have seen? Or do you have special insight that others are lacking? Either way, it might be a good idea to join the discussion in the comments.