LETTER FROM THE EDITOR Dear Colleague, This week we’re highlighting practical ways engineering teams are tackling some of the hardest problems in deploying edge AI and vision systems: getting models to work reliably in the real world, modernizing vision software for new hardware and model architectures, and scaling physical AI beyond the prototype stage. […]
Edge AI and Vision Insights: June 24, 2026 Read More +
This blog post was originally published at Renesas’ website. It is reprinted here with the permission of Renesas. An AI-driven gadget that acts on a drifting signal doesn’t know it’s wrong. It just acts—confidently, precisely, and in the wrong direction. Confidence without accuracy isn’t intelligence. It’s a liability. The gap between what a system is told
AI Goes Horizontal—Analog Goes Deep Read More +
Update: This Webinar has been rescheduled for September 22 at the same time. It was originally scheduled for September 24, 2026. On September 22, 2026 at 9 am PT (noon ET), Petronel Bigioi, CEO at FotoNation, will present the free hour webinar “Always-On Edge Perception Via a Heterogeneous Near-Memory AI Architecture,” organized by the Edge
Free Webinar On Always-On Edge Perception via Near-memory Compute Read More +
Update: This webinar was originally scheduled for September 10, 2026, however, it has been rescheduled for September 17. On September 17, 2026 at 9 am PT (noon ET), Derrick Chang, Senior Product Manager at Qualcomm Technologies, Inc., will present the free hour webinar “How Qualcomm Is Making Computer Vision Accessible Across Edge Verticals,” organized by
Free Webinar On Qualcomm Accessible Computer Vision (QACV) Read More +
Mayank Mangla, AI Product Manager and Systems Architect at MIPS, a GlobalFoundries company presents “No RISC, No Reward: Unlocking Extreme Efficiency in Physical AI with RISC-V” at the May 2026 Embedded Vision Summit. Deployment of neural networks at the edge is often constrained by the rigidity and integration cost of… “No RISC, No Reward: Unlocking
There’s a significant gap between running an AI model on a server and deploying it effectively to constrained edge hardware in the field. A look at the optimization challenges most teams underestimate. This blog post was originally published at Geisel Software’s website. It is reprinted here with the permission of Geisel Software. Edge AI is
Edge AI Optimization: Why Performance at the Edge Is Harder Than It Looks. Read More +
Petronel Bigioi, CEO at FotoNation presents “Always-On Edge Perception Via a Heterogeneous Near-Memory AI Architecture” at the May 2026 Embedded Vision Summit. Always-on perception is becoming a defining capability of next-generation edge devices, from AR glasses and hearables to battery-operated sensors. Yet continuous audio/video and motion understanding runs into two… “Always-On Edge Perception Via a
This blog post was originally published at Tessolve’s website. It is reprinted here with the permission of Tessolve. As semiconductor devices continue to scale down in size and ramp up in performance, one challenge stands out above many others: thermal behavior. Heat isn’t just a byproduct of activity in modern chips; it’s one of the pivotal
Thermal-Aware Testing Strategies for Next-Gen Semiconductor Devices Read More +
Athish Rahul Rao, Staff Software Engineer at Expedera presents “From Compute-Bound to Memory-Bound: Edge AI Architectures for VLMs” at the May 2026 Embedded Vision Summit. Today’s edge AI hardware was built for CNNs, but vision language models (VLMs) have completely different bottlenecks—especially in safety-critical, latency-sensitive applications like in-cabin automotive intelligence.… “From Compute-Bound to Memory-Bound: Edge
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. In part 1 of this series, you explored why multi-robot autonomous mapping is becoming essential for large-scale facilities and what the core components of a modern multi-robot mapping system are. But knowing what a system should
How to Overcome Vision Challenges While Building a Multi-Robot Mapping System (Part 2) Read More +
Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.
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