Washington, DC CDAO Town Hall
September 24, 2024 | 10:00am EDT
September 24, 2024 | 10:00am EDT
Unlock Your Organization’s Knowledge with AI
Participate with your CDAO peers in the Washington, DC community in small, breakout discussions on a mission-critical priority for data leaders. These informal discussions allow you to share your insights and learn from the lessons, approaches and experiences of a diverse group of peers in virtual breakout rooms.
Join fellow CDAOs in the Washington, DC community to discuss:
Focusing on Foundations for AI Readiness
Establishing Measurable Value and Proving ROI
Driving Culture Change to Elevate Data and Analytics Initiatives
Discussion Leaders
Members of the Washington, DC CDAO community will lead the interactive discussion and share lessons learned.
Keith Howard
Pryon
Director of Federal AI Solutions Engineering
Presenter
Alan Wu
Rocket Companies
Director, Head of Data
Discussion Leader
Kanthi Kiran Narayanasetty
Meta Platforms
Head of Data Engineering - Social Impact Products
Discussion Leader
David Ashley
Secret Service
Chief, HUM Business Solutions
Discussion Leader
Delester Brown PhD
United States National Guard
Chief Data Officer
Discussion Leader
Jasmeet Bhatia
Truist
VP, Decision Science Analytics
Discussion Leader
Agenda
September 24, 2024
10:00am - 11:00am EDT
Unlock Your Organization’s Knowledge with AI
Hosted by Pryon
Retrieval-Augmented Generation (RAG) has emerged as a powerful capability to help businesses efficiently access their trusted enterprise knowledge while mitigating the challenges associated with GenAI. An enterprise RAG architecture sets businesses on the path to developing their own Knowledge Cloud, serving up valuable knowledge to users instantly. Though the concept of RAG is straightforward, implementing and scaling it for an enterprise introduces complex challenges.
Join this session to discuss:
- How Generative AI is revolutionizing the future of knowledge-based work
- Core requirements for building an enterprise-ready RAG solution
- Ways organizations can effectively deploy RAG-based AI solutions
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