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DTSTART:20260329T030000
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TZOFFSETTO:+0200
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DTSTART:20251026T020000
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BEGIN:VEVENT
DTSTAMP:20251109T184140Z
UID:3EA1B469-456A-4E87-910B-019FE845E0D6
DTSTART;TZID=Europe/Berlin:20251106T163000
DTEND;TZID=Europe/Berlin:20251106T174500
DESCRIPTION:Workshop_exploring_AI_LLM_RAG_Fine-tunning\n\n[][][]\n\nA works
 hop titled “Large Language Models (LLMs)\, Retrieval-Augmented Generatio
 n (RAG)\, and Fine-Tuning” was held to provide participants with insight
 s into the latest advancements in artificial intelligence and natural lang
 uage processing. The session introduced the fundamentals of large language
  models\, explaining their architecture\, capabilities\, and real-world ap
 plications. It also explored the concept of Retrieval-Augmented Generation
 \, highlighting how integrating external knowledge sources enhances the ac
 curacy and contextual relevance of AI-generated responses. Additionally\, 
 the workshop demonstrated fine-tuning techniques that enable customization
  of pre-trained models for specific domains.\n\nBldg: supcom\, Cité Techn
 ologique des Communications - Rte de Raoued Km 3\,5 - 2083\, Ariana Tunis\
 , tunisie\, Ariana\, Tunisia\, 2080
LOCATION:Bldg: supcom\, Cité Technologique des Communications - Rte de Rao
 ued Km 3\,5 - 2083\, Ariana Tunis\, tunisie\, Ariana\, Tunisia\, 2080
ORGANIZER:khaoula-km@ieee.org
SEQUENCE:27
SUMMARY:workshop_exploring_AI_LLM_RAG_Fine-tunning
URL;VALUE=URI:https://events.vtools.ieee.org/m/513433
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p style=&quot;text-align: center\
 ;&quot;&gt;&lt;span style=&quot;color: rgb(52\, 73\, 94)\;&quot;&gt;&lt;strong&gt;&lt;em&gt;Workshop_exploring
 _AI_LLM_RAG_Fine-tunning&lt;/em&gt;&lt;/strong&gt;&lt;/span&gt;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&lt;img
  src=&quot;https://events.vtools.ieee.org/vtools_ui/media/display/4102077f-9e1a
 -48bd-ab28-aa6f04c169f3&quot; alt=&quot;&quot; width=&quot;300&quot; height=&quot;200&quot;&gt;&lt;img src=&quot;https:/
 /events.vtools.ieee.org/vtools_ui/media/display/b2b9ef16-cb59-4e9b-a0b7-40
 d90401938f&quot; alt=&quot;&quot; width=&quot;300&quot; height=&quot;200&quot;&gt;&lt;img src=&quot;https://events.vtool
 s.ieee.org/vtools_ui/media/display/27652365-0322-4f2e-9c5d-bd665d3d0d7f&quot; a
 lt=&quot;&quot; width=&quot;300&quot;&gt;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;A workshop titled &lt;em data-star
 t=&quot;18&quot; data-end=&quot;105&quot;&gt;&amp;ldquo\;Large Language Models (LLMs)\, Retrieval-Aug
 mented Generation (RAG)\, and Fine-Tuning&amp;rdquo\;&lt;/em&gt; was held to provide
  participants with insights into the latest advancements in artificial int
 elligence and natural language processing. The session introduced the fund
 amentals of large language models\, explaining their architecture\, capabi
 lities\, and real-world applications. It also explored the concept of Retr
 ieval-Augmented Generation\, highlighting how integrating external knowled
 ge sources enhances the accuracy and contextual relevance of AI-generated 
 responses. Additionally\, the workshop demonstrated fine-tuning techniques
  that enable customization of pre-trained models for specific domains.&lt;/p&gt;
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