The abstract approach to AI is still around and fruitful although it may not be fad of the day among the Phronix crowd. For example look at a recent paper by E

The abstract approach to AI is still around and fruitful although it may not be fad of the day among the Phronix crowd. For example look at a recent paper by Ernest Davis, the author of the review linked to above: https://arxiv.org/pdf/2004.13831.pdf https://arxiv.org/pdf/2004.13831.pdf A Review of Winograd Schema Challenge Datasets and Approaches Vid Kocijan1∗ , Thomas Lukasiewicz1,2 , Ernest Davis3 , Gary Marcus4 and Leora Morgenstern5 1University of Oxford 2Alan Turing Institute, London 3New York University 4Robust AI 5Systems & Technology Research / PARC firstname.lastname@cs.ox.ac.uk, davise@cs.nyu.edu, gary.marcus@nyu.edu, leora.morgenstern@gmail.com Abstract: The Winograd Schema Challenge is both a commonsense reasoning and natural language understanding challenge, introduced as an alternative to the Turing test. A Winograd schema is a pair of sentences differing in one or two words with a highly ambiguous pronoun, resolved differently in the two sentences, that appears to require commonsense knowledge to be resolved correctly. The examples were designed to be easily solvable by humans but difficult for machines, in principle requiring a deep understanding of the content of the text and the situation it describes. This paper reviews existing Winograd Schema Challenge benchmark datasets and approaches that have been published since its introduction.