Artificial Intelligence: The Good, the Bad, and the Ugly – Yaser Abu-Mostafa

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    Artificial Intelligence: The Good, the Bad, and the Ugly – Yaser Abu-Mostafa

    Artificial Intelligence: The Good, the Bad, and the Ugly – Yaser Abu-Mostafa

    Jump to the:
    – start of the lecture: 20:01
    – introduction by Professor Harry Atwater: 12:45
    – profile video of Professor Abu-Mostafa: 16:55

    Explore the presentation by topic here: https://work.caltech.edu/watson.html


    ChatGPT has rocked the general public’s perception and expectations of artificial intelligence (AI). In this lecture, Abu-Mostafa will explain the science of AI in plain language and explore how the scientific details illustrate the risks and benefits of AI. Between the extremes of “AI will kill us all” and “AI will solve all our problems,” the science can help us identify what is realistic and what is speculative, and guide us in our planning, legislation, and investment in AI.

    For more information about Professor Abu-Mostafa’s research: https://home.work.caltech.edu/research.html

    About the Series:

    Since 1922, The Earnest C. Watson Lecture Series has brought Caltech’s most innovative scientific research to the public.

    The series is named for Earnest C. Watson, a professor of physics at Caltech from 1919 until 1959. Spotlighting a small selection of the pioneering research Caltech’s faculty is currently conducting, the Watson Lectures are geared toward a general audience, as part of the Institute’s ongoing commitment to benefiting the local community through education and outreach. Through a gift from the estate of Richard C. Biedebach, the lecture series is able to highlight assistant professors’ research each season.

    Caltech’s 2022-2023 Watson Lectures are being presented virtually and can be viewed on Caltech’s YouTube channel: https://bit.ly/Caltech_Watson_Lectures

    For more information on the Watson Lecture Series: https://caltech.edu/watson

    Produced in association with Caltech Academic Media Technologies.
    ©2023 California Institute of Technology
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