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UID:5a82f8cb5814569c31f88c4746cf29cc-413
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DESCRIPTION:Machine Learning and Logic: Fast and Slow Thinking
URL;VALUE=URI:https://www.csa.iisc.ac.in/newweb/event/413/machine-learning-and-logic-fast-and-slow-thinking/
SUMMARY:Computer science seems to be undergoing a paradigm shift. Much of earlier research was conducted in the framework of well-understood formal models. In contrast, some of the hottest trends today shun formal models and rely on massive data sets and machine learning. A cannonical example of this change is the shift in AI from logic programming to deep learning. I will argue that the correct metaphore for this development is not paradigm shift, but paradigm expansion. Just as General Relativity augments Newtonian Mechanics, rather than replace it -- we went to the moon, after all, using Newtonian Mechanics -- data-driven computing augments model-driven computing. In the context of Artificial Intelligence, machine learning and logic correspond to the two modes of human thinking: fast thinking and slow thinking. The challenge today is to integrate the model-driven and data-driven paradigms. I will describe one approach to such an integration -- making logic more quantitative.
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For more details please visit: https://www.csa.iisc.ac.in/theoryseminars/?talk=20230216_MosheVardi
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Link to online talk: 
https://teams.microsoft.com/l/meetup-join/19%3ameeting_ZGE3NDg5NzktMWQ0Zi00MzFmLTg5OTgtMTMyYWM4MWQyYjI2%40thread.v2/0?context=%7b%22Tid%22%3a%226f15cd97-f6a7-41e3-b2c5-ad4193976476%22%2c%22Oid%22%3a%227c84465e-c38b-4d7a-9a9d-ff0dfa3638b3%22%7d
DTSTART:20230216T120000Z
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