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VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:Pacific/Honolulu
BEGIN:STANDARD
DTSTART:19470608T023000
TZOFFSETFROM:-1130
TZOFFSETTO:-1000
TZNAME:HST
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BEGIN:VEVENT
DTSTAMP:20240618T082217Z
UID:026AC07D-9114-4A69-8074-0490D64E339F
DTSTART;TZID=Pacific/Honolulu:20240617T190000
DTEND;TZID=Pacific/Honolulu:20240617T203000
DESCRIPTION:Join us Monday night June 17th from 7PM to 8PM at UH/Manoa Holm
 es Engineering Building room #244 for a seminar presentation by Dr PR. Chi
 dambaram\, Vice President of Engineering at Qualcomm. His talk title is "S
 emiconductor Challenges For Edge Artificial Intelligence Adoption".\n\nAbs
 tract: Edge AI will drive the growth of the consumer electronics industry 
 in the next few years. We will take a look at some of the edge AI systems 
 and what are some of the key semiconductor implementation challenges to ad
 dress the edge AI systems. Lack of leading CMOS scaling\, memory band widt
 h demands and connectivity challenges will be addressed.\n\nSpeaker(s): Ch
 idi Chidambaram\n\nRoom: 244\, Bldg: Holmes Hall\, 2540 Dole St\, Universi
 ty of Hawaii\, Honolulu\, Hawaii\, United States\, 96822
LOCATION:Room: 244\, Bldg: Holmes Hall\, 2540 Dole St\, University of Hawai
 i\, Honolulu\, Hawaii\, United States\, 96822
ORGANIZER:johnoborland@aol.com
SEQUENCE:48
SUMMARY:Seminar on Semiconductor Challenges For Edge Artificial Intelligenc
 e Adoption by Dr. Chidambaram of Qualcomm on June 17th at 7PM
URL;VALUE=URI:https://events.vtools.ieee.org/m/423272
X-ALT-DESC:Description: <br /><p>Join us Monday night June 17th from 7PM to
  8PM at UH/Manoa Holmes Engineering Building room #244 for a seminar prese
 ntation by Dr PR. Chidambaram\, Vice President of Engineering at Qualcomm.
 &nbsp\; His talk title is "Semiconductor Challenges For Edge Artificial In
 telligence Adoption".&nbsp\;</p>\n<p>Abstract:&nbsp\; Edge AI will drive t
 he growth of the consumer electronics industry in the next few years.&nbsp
 \; We will take a look at some of the edge AI systems and what are some of
  the key semiconductor implementation challenges to address the edge AI sy
 stems.&nbsp\; Lack of leading CMOS scaling\, memory band width demands and
  connectivity challenges will be addressed.</p>
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