AI & Functional Safety: AI/ML Definitions and Concepts
- Date
- 2026-08-03
- Location
- Online
- Host
- AI & ML Safety (Functional Safety)
About this event
AI is moving quickly from research and product experimentation into systems where mistakes carry real consequences. This session focuses on a question that matters across autonomy, machine learning, and high-stakes software: what do we actually mean when we say AI, ML, safety, and functional safety, and how should those concepts be understood together? If you work anywhere near intelligent systems, this is a practical chance to get clearer on the language, assumptions, and boundaries that shape serious technical and product decisions. Rather than treating AI as a buzzword, the event centers on definitions and concepts that help teams reason more carefully about safety, capability, risk, and system design. About the Event This online session, AI & Functional Safety: AI/ML Definitions and Co
Who should attend
This session is for people who want sharper language and better judgment around AI/ML in safety-relevant systems. - **You work in AI, ML, or data science** and want a cleaner way to explain what your models do, what they do not do, and how they fit into larger systems. - **You are an engineer working on autonomy, embedded systems, robotics, or system architecture** and need stronger conceptual grounding for discussions about behavior, risk, and responsibility. - **You lead product or technical strategy** and want to make better decisions when teams use terms like AI, ML, and autonomy loosely or interchangeably. - **You operate in safety, assurance, compliance, governance, or risk-related roles** and need more precise definitions to evaluate claims, requirements, and system boundaries. - **You are exploring the overlap between AI and domains like crypto or DeFi** and want a disciplined framework for thinking about intelligent components inside larger digital systems. - **You are curious but serious about the topic** and want an accessible entry point that treats definitions as practical tools, not academic trivia.