BEGIN:VCALENDAR VERSION:2.0 PRODID:-//UC Irvine//CML Seminars//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:AI can Learn from Data. But can it Learn to Reason? X-WR-TIMEZONE:America/Los_Angeles BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20070311T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20071104T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:2023-05-15-guy-van-den-broeck@cml.ics.uci.edu DTSTAMP:20230515T000000Z SEQUENCE:57690 DTSTART;TZID=America/Los_Angeles:20230515T130000 DTEND;TZID=America/Los_Angeles:20230515T140000 SUMMARY:[CML Seminar] Guy Van den Broeck: AI can Learn from Data. But can i t Learn to Reason? LOCATION:Donald Bren Hall 4011 DESCRIPTION:Guy Van den Broeck\, Associate Professor of Computer Science\, University of California\, Los Angeles\n\nTitle: AI can Learn from Data. B ut can it Learn to Reason?\n\nAbstract: Many expect that AI will go from p owering chatbots to providing mental health services\, from advertisement to deciding who is given bail. The expectation is that AI will solve socie ty's problems by simply being more intelligent than we are. Implicit in th is bullish perspective is the assumption that AI will naturally learn to r eason from data: that it can form trains of thought that make sense\, simi lar to how a mental health professional or judge might reason about a case \, or how a mathematician might prove a theorem. This talk will investigat e whether this behavior can be learned from data\, and how we can design t he next generation of AI techniques that can achieve such capabilities\, f ocusing on neuro-symbolic learning and tractable deep generative models.\n \nhttps://cml.ics.uci.edu/seminars/2023-05-15-guy-van-den-broeck X-ALT-DESC;FMTTYPE=text/html:Guy Van den Broeck\, Associ ate Professor of Computer Science\, University of California\, Los Angeles

Title: AI can Learn from Data. But can it Learn to Reason?< br>
Abstract: Many expect that AI will go from powering chatbots to providing mental health services\, from advertisement to deciding who is given bail. The expectation is that AI will solve society's problems by simply being more intelligent than we are. Implicit in this bullish persp ective is the assumption that AI will naturally learn to reason from data: that it can form trains of thought that make sense\, similar to how a men tal health professional or judge might reason about a case\, or how a math ematician might prove a theorem. This talk will investigate whether this b ehavior can be learned from data\, and how we can design the next generati on of AI techniques that can achieve such capabilities\, focusing on neuro -symbolic learning and tractable deep generative models.

https://cml .ics.uci.edu/seminars/2023-05-15-guy-van-den-broeck URL:https://cml.ics.uci.edu/seminars/2023-05-15-guy-van-den-broeck END:VEVENT END:VCALENDAR