From data to decisions: How AI at the edge is transforming military systems
Date: Wednesday, August 19, 2026
Time: 2:00 AM (GMT-04:00) Eastern Time - New York
Duration: 60 minutes
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Artificial intelligence (AI) and edge computing are transforming how military and aerospace systems collect, process, and act on data. Rather than relying solely on centralized processing, platforms increasingly require onboard intelligence to enable real-time decision-making in contested or disconnected environments. From autonomous navigation to sensor fusion and predictive maintenance, AI at the edge is redefining operational capability.
This webinar will explore the hardware and software architectures enabling AI deployment at the tactical edge, including heterogeneous computing platforms, GPUs, FPGAs, and specialized AI accelerators. It will also examine challenges related to power constraints, latency, model optimization, and secure deployment in mission-critical systems.
Attendees will gain insight into how developers balance performance with size, weight, and power (SWaP) requirements while addressing issues such as data integrity, model training pipelines, and lifecycle management. The session will highlight real-world use cases across uncrewed systems, ISR platforms, and electronic warfare applications.
Bill Pilaud
Chief Solutions Architect
LCR Embedded Systems
Bill Pilaud leads system architecture and solution development for LCR Embedded Systems and is a recognized expert in open architecture systems design. Across his 35+ year career, he has held roles at Mercury, Motorola, Curtiss-Wright, Concurrent, Vicor, and Abaco spanning engineering, field applications, sales, product marketing, product line management, and general management. Bill holds a BS in Computer Engineering from Clemson University and an MBA from Northeastern University.
Austin Lindquist
Director of Innovation
Wolf Advanced Technology
As the Director of Innovation at WOLF Advanced Technology, Austin leads R&D, rapid prototyping, and new product design for edge computing and AI imaging solutions in aerospace and defense.
Austin joined WOLF in 2024 and previously served as Senior Engineer of Innovation, developing thermal solutions for high-power embedded systems. Austin holds a Ph.D. in Condensed Matter Physics from the University of Toronto, where he studied quantum systems. His prior experience spans research from automotive thermal system design to implementing quantum algorithms using advanced spectroscopy.
Austin’s expertise plays a vital role in driving WOLF’s continued success with mission-critical innovation and R&D work.