Large Language Models & Modern AI: Foundations for Responsible Adoption - Hybrid Event Final Remind

Value to the Audience

This session offers professionals across sectors a clear, practical way to understand artificial intelligence without technical complexity. By framing AI as an idea, a technology stack, and a set of computational techniques, the presentation helps participants make sense of how modern AI systems work, why they appear increasingly powerful, and where their limitations lie. Using accessible analogies and real-world examples, the talk equips attendees to engage with AI thoughtfully—supporting better decision-making, risk awareness, and responsible adoption in organizational, operational, and quality-improvement contexts.

Key Takeaways

• A conceptual framework to understand AI beyond hype, distinguishing core ideas from underlying technologies and tools
• Clear differentiation between machine learning, deep learning, and generative/agentic AI, and what each can and cannot do
• Practical insight into risk, bias, and governance considerations essential for responsible and quality-driven AI use

Uday Pratap Singh is a healthcare data scientist and quality improvement researcher, currently pursuing his PhD at UTHealth Houston, with training in dentistry, oral medicine, and biomedical informatics. His work focuses on making artificial intelligence understandable and useful for professionals across disciplines, particularly in quality improvement and health systems. Through his academic work and engagement with the American Society for Quality, he emphasizes responsible AI adoption, risk awareness, and governance—helping organizations move beyond hype toward thoughtful, quality-centered use of emerging technology.

See you all tomorrow at the event!!!!