With artificial intelligence stepping off the laptop and out onto job sites, factory floors, and flight decks, are we preparing students for the AI that sees, senses, and acts in the real world, not just the kind that chats back?

Matt Kirchner sits down with Lieutenant General Brian Cavanaugh, USMC (Ret.), CEO of VigilanteX. After decades commanding Marines and integrating emerging tech into national defense, Cavanaugh now leads a company building applied AI platforms at the edge: solar- and Starlink-powered trailers with cameras and compute that monitor sites 24/7 and turn video into real-time safety, security and efficiency intelligence.

Together, Matt and Brian unpack what “applied AI” really means across the edge-to-cloud continuum. They discuss AI agents running on the edge, natural language search over video, and systems that close the loop from sensor to decision in seconds. They also explore why simply teaching students to prompt chatbots isn’t enough, and how K-12, CTE, and higher education can catch up to a world where AI is baked into every system, every site, and every mission.

Listen to learn:

• How VigilanteX combines solar power, Starlink, cameras, and edge compute into their tech.
• The difference between AI at the edge and AI in the cloud, and why latency, bandwidth, and resilience matter for safety-critical environments.
• How AI agents work at the edge, and why they can work faster and more efficiently than humans (freeing up humans to do more interesting work).
• Why Cavanaugh believes every student should understand how data moves from sensors to the edge, to the cloud, and back into real-time control.
• What China’s national push for AI education signals about global competition and how U.S. educators should respond with applied AI in the classroom.

➡️ Watch the Full Episode on YouTube

3 Big Takeaways from this Episode:

1. AI at the edge is becoming a digital teammate. VigilanteX’s platforms use cameras, connectivity, and on-site compute to watch for fall risks, PPE issues, intrusions, and abnormal conditions across construction, manufacturing, logistics, and energy sites. The system flags events in real time, routes the right video to supervisors, and builds a data trail leaders can use to change procedures before accidents happen.

2. Edge-to-cloud literacy is a new baseline skill for technical careers. Cavanaugh and Kirchner break down how raw sensor and video data is processed locally, filtered, and then pushed to the cloud for storage, analytics, and dashboards. Understanding where computation lives, what data moves, and how AI agents plug into that pipeline prepares students for roles in automation, OT/IT, robotics, and cyber-physical systems in any industry.

3. We need to teach applied AI, not just chatbots. While large language models are powerful, the episode shows how AI is part of the edge-to-cloud continuum. Giving students hands-on experience with autonomous systems, computer vision, and industrial data flows helps them see AI as something they can design, deploy, and govern rather than a black box that only lives in a browser.

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