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DTSTAMP:20250417T003420Z
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DESCRIPTION:This is a hybrid in-person and online event. Pre-registration i
 s required for either.\n\nAgentic AI\, also known as Autonomous AI\, is a 
 type of AI that is able to independently design\, execute\, and optimize w
 orkflows. Its recent emergence marks a dramatic shift towards more autonom
 ous\, decision-making entities capable of planning\, reasoning\, and takin
 g actions in complex environments.\n\nIn this talk\, Prasad Venkatachar wi
 ll explore the core distinctions between Generative AI (Gen AI) and Agenti
 c AI\, highlighting key characteristics\, technological advancements\, and
  applications across various industries. He will also delve into how it’
 s possible to navigate from passive content generation in Gen AI to active
  problem-solving intelligence. This is done using the core building blocks
  of the Agentic AI architecture by way of retrieval augmented generation (
 RAG)\, the leading technique for enhancing large language models (LLMs) wi
 th enterprise data.\n\nSpeaker(s): Prasad Venkatachar\, \n\n673 South Milp
 itas Blvd.\, Milpitas\, California\, United States\, 95035\, Virtual: http
 s://events.vtools.ieee.org/m/471234
LOCATION:673 South Milpitas Blvd.\, Milpitas\, California\, United States\,
  95035\, Virtual: https://events.vtools.ieee.org/m/471234
ORGANIZER:dmsnyder@ieee.org
SEQUENCE:22
SUMMARY:Agentic AI: The Next Evolution of Generative AI
URL;VALUE=URI:https://events.vtools.ieee.org/m/471234
X-ALT-DESC:Description: <br /><p><strong>This is a hybrid in-person and onl
 ine event. Pre-registration is required for either.</strong></p>\n<p>Agent
 ic AI\, also known as Autonomous AI\, is a type of AI that is able to inde
 pendently design\, execute\, and optimize workflows. Its recent emergence 
 marks a dramatic shift towards more autonomous\, decision-making entities 
 capable of planning\, reasoning\, and taking actions in complex environmen
 ts.</p>\n<p>In this talk\, Prasad Venkatachar will explore the core distin
 ctions between Generative AI (Gen AI) and Agentic AI\, highlighting key ch
 aracteristics\, technological advancements\, and applications across vario
 us industries. He will also delve into how it&rsquo\;s possible to navigat
 e from passive content generation in Gen AI to active problem-solving inte
 lligence. This is done using the core building blocks of the Agentic AI ar
 chitecture by way of retrieval augmented generation (RAG)\, the leading te
 chnique for enhancing large language models (LLMs) with enterprise data.</
 p>
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