Convolutional Neural Networks, AI, and the Physical Limits of Computing with Andrew Lison

November 19, 3:30-5:00pm

It is commonly held that recent advances in “artificial intelligence” have largely been possible due to recent increases in computing power. Moreover, it has long been an engineering assumption, emblematized by Gordon E. Moore's “law,” that this power will continue to improve over time. This talk interrogates the first assumption by way of the increasing untenability of the second: rather than a resurgence enabled by improvements in computation, the recent prominence of AI, it argues, is due to machine learning's potential for exploiting a material computational basis that is in the process of losing its dynamism.

Co-presented by the Technoculture Humanities Institute Research Workshop and the Digital Scholarship Studio and Network.

To RSVP, please visit https://booking.lib.buffalo.edu/event/6714336