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BEGIN:DAYLIGHT
DTSTART:20260329T030000
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DTSTART:20261025T020000
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DTSTAMP:20260920T173148Z
UID:E1C61A3E-C82A-403D-9B57-DF9B7CB16A6A
DTSTART;TZID=CET:20260916T144500
DTEND;TZID=CET:20260916T153000
DESCRIPTION:The increasing demand for real-time intelligence at the edge ne
 cessitates a transition from conventional von Neumann architectures toward
  more energy-efficient and reduced-latency alternatives. This talk explore
 s the concept of analog neuromorphic computing which mimics the biological
  neural processes by leveraging the continuous physical properties of elec
 tronic devices. The physical hardware deployment of analog neuromorphic co
 mputing provides massive parallelism and superior energy efficiency compar
 ed to discretized digital logic systems.\n\nSpeaker(s): Paweł Sitarz\, \n
 \nRoom: 201\, Bldg: Centre of Mechatronics\, Biomechanics and Nanoengineer
 ing\, Poznan University of Technology\, ul. Jana Pawla II 24\, Poznan\, Wi
 elkopolskie\, Poland\, 61-139\, Virtual: https://events.vtools.ieee.org/m/
 577867
LOCATION:Room: 201\, Bldg: Centre of Mechatronics\, Biomechanics and Nanoen
 gineering\, Poznan University of Technology\, ul. Jana Pawla II 24\, Pozna
 n\, Wielkopolskie\, Poland\, 61-139\, Virtual: https://events.vtools.ieee.
 org/m/577867
ORGANIZER:tomasz.marciniak@put.poznan.pl
SEQUENCE:25
SUMMARY:Analog Neuromorphic Computing for Edge-AI
URL;VALUE=URI:https://events.vtools.ieee.org/m/577867
X-ALT-DESC:Description: &lt;br /&gt;&lt;p class=&quot;Abstract&quot; style=&quot;margin-bottom: 0cm
 \;&quot;&gt;The increasing demand for real-time intelligence at the edge necessita
 tes a transition from conventional von Neumann architectures toward more e
 nergy-efficient and reduced-latency alternatives. This talk explores the c
 oncept of analog neuromorphic computing which mimics the biological neural
  processes by leveraging the continuous physical properties of electronic 
 devices. The physical hardware deployment of analog neuromorphic computing
  provides massive parallelism and superior energy efficiency compared to d
 iscretized digital logic systems.&lt;/p&gt;
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