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DTSTART:20260308T030000
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DTSTAMP:20260418T221954Z
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DTSTART;TZID=America/Denver:20260415T180000
DTEND;TZID=America/Denver:20260415T193000
DESCRIPTION:Presentation: Building Intelligent Commerce Using Generative an
 d Multimodal AI\n\nAbstract: This talk explores how generative and multimo
 dal AI systems are transforming product discovery\, personalization\, and 
 decision making in modern retail environments. The session explains how se
 arch engines and product platforms combine embeddings\, retrieval models\,
  and multimodal understanding to interpret both images and text. The talk 
 also covers how generative models create content across text\, imagery\, a
 nd layout structures\; how quality\, safety\, and approval systems validat
 e content before publication\; and how these pipelines are deployed at sca
 le in consumer-facing products. The session concludes with an outlook on n
 ext generation agent based automation\, multimodal model capabilities\, an
 d emerging research directions. The content is designed to be accessible t
 o students\, engineers\, and AI enthusiasts without requiring deep familia
 rity with low-level systems.\n\nSpeaker(s): Vasanth Rajendran\, \n\nVirtua
 l: https://events.vtools.ieee.org/m/555002
LOCATION:Virtual: https://events.vtools.ieee.org/m/555002
ORGANIZER:gowansj@ieee.org
SEQUENCE:10
SUMMARY:CIR & CIS: Building Intelligent Commerce Using Generative and Multi
 modal AI
URL;VALUE=URI:https://events.vtools.ieee.org/m/555002
X-ALT-DESC:Description: <br /><div class="presentation-title"><strong>Prese
 ntation: Building Intelligent Commerce Using Generative and Multimodal AI<
 /strong></div>\n<div class="abstract">&nbsp\;</div>\n<div class="abstract"
 ><strong>Abstract:</strong> This talk explores how generative and multimod
 al AI systems are transforming product discovery\, personalization\, and d
 ecision making in modern retail environments. The session explains how sea
 rch engines and product platforms combine embeddings\, retrieval models\, 
 and multimodal understanding to interpret both images and text. The talk a
 lso covers how generative models create content across text\, imagery\, an
 d layout structures\; how quality\, safety\, and approval systems validate
  content before publication\; and how these pipelines are deployed at scal
 e in consumer-facing products. The session concludes with an outlook on ne
 xt generation agent based automation\, multimodal model capabilities\, and
  emerging research directions. The content is designed to be accessible to
  students\, engineers\, and AI enthusiasts without requiring deep familiar
 ity with low-level systems.</div>
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