AI at the Edge is a different operating environment
Practical AI · 2026-03-25 · 47 min
Episode notes
What does “AI at the edge” really mean in 2026, and why does it matter now more than ever before? In this episode, we’re joined by Brandon Shibley, Edge AI Solutions Engineering Lead at Qualcomm’s Edge Impulse, to discuss the current state and future of Edge AI in 2026. We discuss Gen AI, Small Models, and Cascades of Models, along with real-world constraints like latency, power, and privacy. We also dive into the role of MLOps, evolving hardware, and how developers can start building practical edge AI systems today. Featuring: Brandon Shibley - LinkedIn Chris Benson - Website , LinkedIn , Bluesky , GitHub , X Daniel Whitenack - Website , GitHub , X Links: Read our Ultimate Guide to Edge AI Download your copy of O'Reilly's AI at the Edge Check out the Edge Impulse blog
More from Practical AI
All episodes →- AIUC-1: Building trust in AI agents74 / 100
- Zero Trust for AI Agents61 / 100
- Breaking down the 2026 Stanford AI Index Report53 / 100
- Rebooting Enterprise AI with MCP and Kubernetes
- Hermes Agent: Agents that grow with you