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DESCRIPTION:Click for Latest Location Information: http://dgiq2024east.data
 versity.net/sessionPop.cfm?confid=162&proposalid=15627\nNOTE: This Seminar 
 continues to Friday.\n\nThe hype of Generative AI is rapidly dissipating as
  organizations rapidly normalize the adoption of large language models (LLM
 s) and other AI and machine learning techniques. Many organizations are pil
 oting and assessing the business value of LLMs and generative AI techniques
 . Yet because of the need for greater technological depth, those tasked wit
 h evaluating these technologies may misunderstand how these emergent AI env
 ironments and models are trained, fine-tuned, and produce results, resultin
 g in raised expectations about both the trustworthiness of the outputs and 
 the implications for misinterpreting produced results.\n\nIn these nascent 
 AI implementations, risks abound – whether the AI systems produce hal
 lucinations, are subject to integrated bias, inadvertently expose sensitive
  data or open other information vulnerabilities. Allowing these systems to 
 run in an ungoverned manner only magnifies these issues. There are ways tha
 t existing knowledge management techniques can mitigate these risks, and in
  this tutorial, we explore ways that taxonomies, ontologies, and knowledge 
 graphs can lend credibility and increased trustworthiness to an AI implemen
 tation.\n\nAttendees will learn about:\n\n
 Information risks associated with emergent AI technologies\n
 Establishing the case for trusted AI\n
 Fundamentals of Semantic Data Modeling\n
 Introduction to taxonomies, ontologies, and knowledge graphs\n
 Practical integration of semantic technologies with AI implementations\n\n
DTSTART:20241212T083000
SUMMARY:S2: Applying Semantic Technologies to AI Governance and Information
  Risk Mitigation
DTEND:20241212T155959
LOCATION: See Description
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