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PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20260308T030000
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DTSTART:20261101T010000
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BEGIN:VEVENT
DTSTAMP:20260424T013721Z
UID:1009FA31-1346-4B48-B351-BF26D3DA5156
DTSTART;TZID=America/New_York:20260420T180000
DTEND;TZID=America/New_York:20260420T190000
DESCRIPTION:While the chatter about AI is incessant\, many people are unawa
 re of the intricacies of effective AI deployment at data centers. Yet\, it
 &#39;s exactly this architecture that provides the scaffolding for tools such 
 as ChatGPT\, Nano Banana\, and Copilot. If you&#39;re curious about how AI is 
 operationalized on a large-scale and the specific hardware pieces that mak
 e it possible\, then you are in luck. Tuesday\, April 20th\, join Nainsi J
 ain as she provides a technical walkthrough of the end-to-end process of s
 caling hyperscale data center infrastructure — from interpreting custome
 r demand signals to physical rack deployment — and how AI-driven capacit
 y planning is making that process faster and more reliable\n\nVirtual: htt
 ps://events.vtools.ieee.org/m/548034
LOCATION:Virtual: https://events.vtools.ieee.org/m/548034
ORGANIZER:aj.williams@ieee.org
SEQUENCE:43
SUMMARY:From Demand Signal to Deployed Rack: Building AI-Driven Capacity Pl
 anning Systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/548034
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;While the chatter about AI is incessant\, 
 many people are unaware of the intricacies of effective AI deployment at d
 ata centers. Yet\, it&#39;s exactly this architecture that provides the scaffo
 lding for tools such as ChatGPT\, Nano Banana\, and Copilot. If you&#39;re cur
 ious about how AI is operationalized on a large-scale and the specific har
 dware pieces that make it possible\, then you are in luck. Tuesday\, April
  20th\, join Nainsi Jain as she provides a technical walkthrough of the en
 d-to-end process of scaling hyperscale data center infrastructure &amp;mdash\;
  from interpreting customer demand signals to physical rack deployment &amp;md
 ash\; and how AI-driven capacity planning is making that process faster an
 d more reliable&lt;/p&gt;
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