Interessierte sind herzlich eingeladen am Dienstag, 28. Mai 2024 um 16:00 Uhr in den Hermann-Krone-Bau der TU Dresden zu kommen (Raum 1.11) und Prof. Dr. Kwabena Boahen von der Stanford University zu hören. Der Vorlesungstitel lautet: „Scaling Knowledge Processing from 2D Chips to 3D Brains“ und die Vorlesung endet um 17:30 Uhr.

Sollten Sie die Vorlesung lieber online verfolgen wollen, finden Sie hier den Link zur Videokonferenz.

Abstract:

As a computer's processors increase in number, they process data at a higher
rate and exchange results across a greater distance. Thus, the computer
consumes energy at a rate that increases quadratically. In contrast, as a brain's
neurons increase in number, it consumes energy at a rate that increases not
quadratically but rather just linearly. Thus, an 86B-neuron human brain
consumes not 2 terawatts but rather just 25 watts. To scale linearly rather than
quadratically, the brain follows two design principles. First, pack neurons in
three dimensions (3D) rather than just two (2D). This principle shortens wires
and thus reduces the energy a signal consumes as well as the heat it
generates. Second, scale the number of signals per second as the square-root
of the number of neurons rather than linearly. This principle matches the heat
generated to the surface area available and thus avoids overheating. I will
illustrate how we could apply these two principles to design AI hardware that
runs not with megawatts in the cloud but rather with watts on a phone.