How can AI support faster, more resilient decisions when connectivity is limited and the stakes are high?

In this week’s episode of Feds at the Edge, we sit down with experts who have experience bringing AI into the field, from nuclear research facilities to remote military environments.

Chris Ritter with INL discusses the growing popularity of AI models that run locally and how autonomous laboratory systems can reduce the time required for research and experimentation. Dan Folliard of Astra AI explores how AI can address the size, weight, and power constraints of remote military environments.

We’ll also highlight a critical factor in bringing AI to the edge: trust. Open architecture, modularity, model registries, experimentation, and small initial wins can help stakeholders build confidence and accelerate adoption.

Tune in on your favorite podcasting platform as government and industry experts explore practical approaches to deploying AI in disconnected, bandwidth-constrained, contested, and high-consequence environments.

To view this webinar: AI at the Edge: Turning Promise into Mission Advancement.

Featured Speakers:

Chris Ritter, Division Director, Scientific Computing & AI and Director, Digital Innovation Center of Excellence, Idaho National Laboratory

Chris Ritter
Division Director, Scientific Computing & AI
and Director, DICE,
Idaho National Laboratory
Tracy Mills, Distinguished Chief Technologist, U.S. Public Sector Federal Systems Integrators, HPE

Tracy Mills
Distinguished Chief Technologist, U.S. Public
Sector Federal Systems Integrators, HPE
Daniel Folliard, DOD Strategic Advisor, Astris AI

Daniel Folliard
DoD Strategic Advisor,
Astris AI
John Breeden II, Moderator & Contributing Editor, FedInsider

John Breeden II
Moderator & Contributing Editor,
FedInsider

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