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SUMMARY:Reliable and Sustainable AI: From Mathematical Foundations to Next
  Generation AI Computing - Gitta Kutyniok\, Ludwig-Maximilians-Universitä
 t München
DTSTART:20251204T150000Z
DTEND:20251204T160000Z
UID:TALK237136@talks.cam.ac.uk
CONTACT:Matthew Colbrook
DESCRIPTION:The current wave of artificial intelligence is transforming in
 dustry\, society\, and the sciences at an unprecedented pace. Yet\, despit
 e its remarkable progress\, today’s AI still suffers from two major limi
 tations: a lack of reliability and excessive energy consumption.\n\nThis l
 ecture will begin with an overview of this dynamic field\, focusing first 
 on reliability. We will present recent theoretical advances in the areas o
 f generalization and explainability -- core aspects of trustworthy AI that
  also intersect with regulatory frameworks such as the EU AI Act. From the
 re\, we will explore fundamental limitations of existing AI systems\, incl
 uding challenges related to computability and the energy inefficiency of c
 urrent digital hardware. These challenges highlight the pressing need to r
 ethink the foundations of AI computing.\n\nIn the second part of the talk\
 , we will turn to neuromorphic computing -- a promising and rapidly evolvi
 ng paradigm that emulates biological neural systems using analog hardware.
  We will introduce spiking neural networks\, a key model in this area\, an
 d share some of our recent mathematical findings. These results point towa
 rd a new generation of AI systems that are not only provably reliable but 
 also sustainable.
LOCATION:Centre for Mathematical Sciences\, MR14
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