BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Europe/Berlin
BEGIN:DAYLIGHT
DTSTART:20260329T030000
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20261025T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260505T134445Z
UID:7F637D53-F10A-41AF-B430-6C264F31B4AB
DTSTART;TZID=Europe/Berlin:20260518T153000
DTEND;TZID=Europe/Berlin:20260518T173000
DESCRIPTION:Abstract: Analog/mixed-signal integrated circuits are key in ap
 plications where electronics interface with the physical world. The design
  of analog circuits\, however\, is time consuming and prone to errors\, of
 ten requiring multiple redesign cycles. The rebirth of AI and machine lear
 ning\, and the recent rise of generative AI methods\, on the other hand\, 
 create a whole new spectrum of techniques to automate this process. This i
 nvited talk will explore the high potential of using advanced machine lear
 ning (ML) techniques to automatically synthesize and lay out analog integr
 ated circuits. What is hype and what will be feasible? Will we still need 
 analog designers in the future and how will they operate?\n\nCo-sponsored 
 by: NXP Semiconductors Germany GmbH\n\nSpeaker(s): \, Georges Gielen\n\nSc
 hatzbogen 7\, Munich\, Bayern\, Germany\, 81829 \, Virtual: https://events
 .vtools.ieee.org/m/551113
LOCATION:Schatzbogen 7\, Munich\, Bayern\, Germany\, 81829 \, Virtual: http
 s://events.vtools.ieee.org/m/551113
ORGANIZER:mohamed.faragalla@ieee.org
SEQUENCE:24
SUMMARY:Who will design tomorrow&#39;s analog integrated circuits: humans or AI
 -based synthesis?
URL;VALUE=URI:https://events.vtools.ieee.org/m/551113
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;&lt;span style=&quot;font-family: arial\, helvetic
 a\, sans-serif\; font-size: 18pt\;&quot;&gt;Abstract: Analog/mixed-signal integrat
 ed circuits are key in applications where electronics interface with the p
 hysical world. The design of analog circuits\, however\, is time consuming
  and prone to errors\, often requiring multiple redesign cycles. The rebir
 th of AI and machine learning\, and the recent rise of generative AI metho
 ds\, on the other hand\, create a whole new spectrum of techniques to auto
 mate this process. This invited talk will explore the high potential of us
 ing advanced machine learning (ML) techniques to automatically synthesize 
 and lay out analog integrated circuits. What is hype and what will be feas
 ible? Will we still need analog designers in the future and how will they 
 operate?&lt;/span&gt;&lt;/p&gt;
END:VEVENT
END:VCALENDAR

