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DESCRIPTION:IEEE SCV WIE AI Summit 2026\n\n[]\n\nIn an era where AI technol
 ogies are rapidly transforming industries and redefining possibilities\, i
 t is crucial to explore both the innovations driving this change and the r
 esponsibilities that come with it. Today\, we will delve into a diverse ar
 ray of topics that highlight the multifaceted nature of AI and its profoun
 d impact on our lives.\n\nOur sessions will cover the latest developments 
 in Large Language Models and Foundation Models\, exploring efficient fine-
 tuning\, multilingual adaptation\, and the role of LLMs as knowledge bases
 . We will also examine the evolution of AI agents\, focusing on autonomous
  task completion\, multi-agent collaboration\, and the integration of exte
 rnal knowledge for robust decision-making.\n\nIn the realm of Vision and M
 ultimodality\, we will explore the integration of text\, image\, and video
  understanding\, as well as advanced techniques like zero-shot learning an
 d self-supervised learning. Our discussions on MLOps for LLMs will provide
  insights into best practices for training\, deploying\, and evaluating la
 rge models.\n\nWe will also address the critical areas of Knowledge-Ground
 ed Reasoning\, On-Device Learning\, and the ethical dimensions of AI\, inc
 luding bias mitigation\, privacy preservation\, and the detection of misin
 formation.\n\nTalk tracks are broadly classified but not limited to\,\n1. 
 Large Language Models (LLMs) &amp; Foundation Models\n2. AI Agents\n3. Sustain
 able Hardware for AI\n4. Edge to Cloud Orchestration\n5. Knowledge-Grounde
 d &amp; Reasoning\n6. On-Device Learning for LLMs and Multi-Modal AI\n7. Ethic
 s\, Bias &amp; Fairness\n8. Women Leading the AI Revolution\n\nAgenda: \nTBD\n
 \nBldg: SC12\, Intel\, 3600 Juliette Ln\, Santa Clara\, CA 95054\, US\, Sa
 nta Clara\, California\, United States\, 95054
LOCATION:Bldg: SC12\, Intel\, 3600 Juliette Ln\, Santa Clara\, CA 95054\, U
 S\, Santa Clara\, California\, United States\, 95054
ORGANIZER:sbehere@ieee.org
SEQUENCE:20
SUMMARY:IEEE SCV WIE AI Summit 2026
URL;VALUE=URI:https://events.vtools.ieee.org/m/572127
X-ALT-DESC:Description: &lt;br /&gt;&lt;div class=&quot;ahS2Le&quot;&gt;\n&lt;h1 class=&quot;F9yp7e ikZYw
 f LgNcQe&quot; dir=&quot;auto&quot; role=&quot;heading&quot; aria-level=&quot;1&quot;&gt;IEEE SCV WIE AI Summit 
 2026&lt;/h1&gt;\n&lt;p&gt;&lt;img src=&quot;https://events.vtools.ieee.org/vtools_ui/media/dis
 play/713b6f53-1557-42fd-9832-17e5dcd32d35&quot; alt=&quot;&quot; width=&quot;916&quot; height=&quot;916&quot;
 &gt;&lt;/p&gt;\n&lt;/div&gt;\n&lt;p&gt;&lt;em&gt;In an era where AI technologies are rapidly transfor
 ming industries and redefining possibilities\, it is crucial to explore bo
 th the innovations driving this change and the responsibilities that come 
 with it. Today\, we will delve into a diverse array of topics that highlig
 ht the multifaceted nature of AI and its profound impact on our lives.&lt;/em
 &gt;&lt;/p&gt;\n&lt;p&gt;&lt;em&gt;Our sessions will cover the latest developments in Large Lan
 guage Models and Foundation Models\, exploring efficient fine-tuning\, mul
 tilingual adaptation\, and the role of LLMs as knowledge bases. We will al
 so examine the evolution of AI agents\, focusing on autonomous task comple
 tion\, multi-agent collaboration\, and the integration of external knowled
 ge for robust decision-making.&lt;/em&gt;&lt;/p&gt;\n&lt;p&gt;&lt;em&gt;In the realm of Vision and
  Multimodality\, we will explore the integration of text\, image\, and vid
 eo understanding\, as well as advanced techniques like zero-shot learning 
 and self-supervised learning. Our discussions on MLOps for LLMs will provi
 de insights into best practices for training\, deploying\, and evaluating 
 large models.&lt;/em&gt;&lt;/p&gt;\n&lt;p&gt;&lt;em&gt;We will also address the critical areas of 
 Knowledge-Grounded Reasoning\, On-Device Learning\, and the ethical dimens
 ions of AI\, including bias mitigation\, privacy preservation\, and the de
 tection of misinformation.&lt;/em&gt;&lt;/p&gt;\n&lt;p&gt;Talk tracks are broadly classified
  but not limited to\,&lt;/p&gt;\n&lt;div&gt;&lt;span dir=&quot;ltr&quot;&gt;1.&amp;nbsp\;&lt;strong&gt;Large Lan
 guage Models (LLMs) &amp;amp\; Foundation Models&lt;/strong&gt;&lt;/span&gt;&lt;/div&gt;\n&lt;div&gt;&lt;
 span dir=&quot;ltr&quot;&gt;&lt;strong&gt;2. AI Agents&lt;/strong&gt;&lt;/span&gt;&lt;/div&gt;\n&lt;div&gt;&lt;span dir=
 &quot;ltr&quot;&gt;&lt;strong&gt;3. Sustainable Hardware for AI&lt;/strong&gt;&lt;/span&gt;&lt;/div&gt;\n&lt;div&gt;&lt;
 span dir=&quot;ltr&quot;&gt;&lt;strong&gt;4. Edge to Cloud Orchestration&lt;/strong&gt;&lt;/span&gt;&lt;/div
 &gt;\n&lt;div&gt;&lt;span dir=&quot;ltr&quot;&gt;&lt;strong&gt;5. Knowledge-Grounded &amp;amp\; Reasoning&lt;/st
 rong&gt;&lt;/span&gt;&lt;/div&gt;\n&lt;div&gt;&lt;strong&gt;&lt;span dir=&quot;ltr&quot;&gt;6. &lt;/span&gt;On-Device Learn
 ing for LLMs and Multi-Modal AI&lt;/strong&gt;&lt;/div&gt;\n&lt;div&gt;&lt;span dir=&quot;ltr&quot;&gt;&lt;stro
 ng&gt;7. Ethics\, Bias &amp;amp\; Fairness&lt;/strong&gt;&lt;/span&gt;&lt;/div&gt;\n&lt;div&gt;&lt;span dir=
 &quot;ltr&quot;&gt;&lt;strong&gt;8. Women Leading the AI Revolution&lt;/strong&gt;&lt;/span&gt;&lt;/div&gt;\n&lt;d
 iv&gt;&lt;span dir=&quot;ltr&quot;&gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;&lt;/span&gt;&lt;/div&gt;&lt;br /&gt;&lt;br /&gt;Agenda
 : &lt;br /&gt;&lt;div dir=&quot;ltr&quot;&gt;\n&lt;div&gt;TBD&lt;/div&gt;\n&lt;/div&gt;
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