AI systems can produce impressive demos and still fail when exposed to real-world complexity, edge cases, changing data, and unexpected user behavior. Semiconductor engineers have spent decades addressing a similar problem through rigorous verification, coverage analysis, corner-case testing, fault injection, regression, and disciplined sign-off. This talk explores how those principles can be adapted to the evaluation of LLMs and increasingly autonomous AI agents, where a successful prompt or benchmark score is not sufficient evidence of system reliability. Attendees will leave with a practical framework for moving from “the AI works” to “we have evidence that this AI system is ready to deploy.”
Dr. Felix Njeh is a computer engineer, AI researcher, professor, author, and semiconductor engineering leader with decades of experience spanning hardware and system validation, AI/ML, edge computing, and intelligent systems. His engineering work includes semiconductor validation and verification at Intel and AI/ML systems research supporting advanced defense applications. He teaches graduate-level computing courses and is the author of Beyond Limits: AI-Powered Edge Architecture for Smart Devices and AI Unlocked: Harnessing Machines Without Losing Your Humanity. He is also Founder of the AI Crusaders Global Network™, an international initiative advancing practical, responsible, and human-centered AI education and adoption.
