We are happy to announce that Embedl will be attending EDGE AI San Diego 2026, the flagship global event for the edge AI community, taking place March 24 to 26 in San Diego.
Hosted by the EDGE AI Foundation, this in-person conference brings together developers, researchers, industry leaders, and decision makers focused on deploying AI at the edge. The event will be held at Eve, a waterfront venue in downtown San Diego, and features three days of keynotes, panels, workshops, roundtables, demos, and networking opportunities designed to accelerate the transition from experimentation to real world impact.
Edge AI is transforming industries such as automotive, robotics, defense, and industrial automation. EDGE AI San Diego provides a unique opportunity to connect with the community driving this transformation while exploring practical deployment strategies and emerging technologies.
Key themes of the conference include building efficient AI models for constrained hardware environments, managing latency and power requirements, scaling edge deployments from prototypes to production, and bridging the gap between research innovation and operational systems.
We are proud to share that Richard Savage, Chief Sales Officer at Embedl, will deliver a featured talk:
What Defense Can Learn from Autonomous Driving About Building Mission Ready Edge AI
March 26, 11:50 AM to 12:10 PM
Mainstage
Defense organizations face challenges similar to those in the autonomous driving industry, particularly the need to deliver reliable, efficient AI at the edge under strict latency, power, and environmental constraints.
As missions increasingly depend on rapid autonomous decision making from large multimodal sensor streams, traditional server centric AI pipelines become impractical. Limited connectivity, scarce bandwidth, and the risks introduced by data offloading make on device intelligence essential.
Autonomous driving addressed these constraints through hardware aware model development, continuous validation workflows, and highly optimized edge deployment strategies. This session explores how these proven methodologies can translate to defense edge AI programs.
Topics covered include early hardware in the loop profiling, quantization and structured compression to meet SWaP limits, mixed precision strategies that balance accuracy and efficiency, automated architecture search aligned with mission KPIs and computational budgets, and principles such as reproducibility, deterministic builds, and rapid iteration.
Using real world examples including UAS perception, EO and IR situational awareness, multi sensor fusion, and low power unattended sensing, the talk demonstrates how automotive grade approaches can improve latency, robustness, and power efficiency at the tactical edge.
The session emphasizes practical workflows that organizations can adopt immediately. These include defining mission constraints early in development, curating representative datasets, profiling performance on target hardware, and validating solutions in mission like environments.
As communications degrade and sensing becomes more distributed, defense platforms increasingly rely on fast, dependable, and power efficient AI running directly at the edge. By adopting lessons from autonomous driving, the defense community can build edge AI pipelines that are more predictable, resilient, and mission ready.
If you are attending EDGE AI San Diego 2026, we would love to connect. Join us to discuss how Embedl helps organizations optimize and deploy efficient AI models that perform reliably under real world constraints.
Stay tuned for more updates, schedule a meeting here and we hope to see you in San Diego.