Videos on Edge AI and Visual Intelligence
We hope that the compelling AI and visual intelligence case studies that follow will both entertain and inspire you, and that you’ll regularly revisit this page as new material is added. For more, monitor the News page, where you’ll frequently find video content embedded within the daily writeups.
Alliance Website Videos
“Porting and Optimizing Advanced Vision-Language-Action Models for Embedded Autonomous Systems,” a Presentation from Quadric
Mike Leonard, Software Architect at Quadric presents “Porting and Optimizing Advanced Vision-Language-Action Models for Embedded Autonomous Systems” at the May 2026 Embedded Vision Summit. World-scale vision-language-action (VLA) models are the new frontier in AI for autonomous driving and robotics, enabling systems to perceive, reason and act in complex real-world environments.… “Porting and Optimizing Advanced Vision-Language-Action
“How to Train an AI Model Using Roboflow and Deploy to an MCU with an NPU,” a Presentation from OpenMV
Kwabena Agyeman, Joseph Nelson, President at OpenMV presents “How to Train an AI Model Using Roboflow and Deploy to an MCU with an NPU” at the May 2026 Embedded Vision Summit. Running computer vision on microcontrollers is becoming practical thanks to MCUs that integrate NPUs, enabling low-latency inference with tight… “How to Train an AI
“COOL: Accelerating Computer Vision Workloads with Cloud Optimized OpenCV on AWS,” a Presentation from OpenCV.org, Amazon Web Services
Frantz Lohier, Satya Mallick, Senior WW Specialist—Advanced Computing, AI and Robotics at Amazon Web Services presents “COOL: Accelerating Computer Vision Workloads with Cloud Optimized OpenCV on AWS” at the May 2026 Embedded Vision Summit. As computer vision workloads grow in scale and complexity, developers need high-performance, cost-efficient infrastructure to keep… “COOL: Accelerating Computer Vision Workloads
“No RISC, No Reward: Unlocking Extreme Efficiency in Physical AI with RISC-V,” a Presentation from MIPS, a GlobalFoundries company
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
“Always-On Edge Perception Via a Heterogeneous Near-Memory AI Architecture,” a Presentation from FotoNation
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
“From Compute-Bound to Memory-Bound: Edge AI Architectures for VLMs,” a Presentation from Expedera
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
“Navigating Physical AI Deployment Across Multiple Platforms for Automated Optical Inspection,” a Presentation from eInfochips (an Arrow company)
Barrie Mullins, Assistant Vice President at eInfochips (an Arrow company) presents “Navigating Physical AI Deployment Across Multiple Platforms for Automated Optical Inspection” at the May 2026 Embedded Vision Summit. As automated optical inspection moves from the server room to the factory floor, the promise of “seamless” AI deployment often hits… “Navigating Physical AI Deployment Across
“One Silicon, Two Worlds: NPU Optimization for Autoregressive and Diffusion Transformers,” a Presentation from VeriSilicon
Shang-Hung Lin, Vice President of NPU Technology at VeriSilicon presents “One Silicon, Two Worlds: NPU Optimization for Autoregressive and Diffusion Transformers” at the May 2026 Embedded Vision Summit. Physical AI is caught between two computational titans: autoregressive (AR) transformers, which predict discrete action tokens, and diffusion transformers (DiTs), which refine… “One Silicon, Two Worlds: NPU
“Why Edge Vision Models Keep Breaking—and What Complete Training Data Changes,” a Presentation from Synetic
David Scott, Founder and CEO at Synetic presents “Why Edge Vision Models Keep Breaking—and What Complete Training Data Changes” at the May 2026 Embedded Vision Summit. Most edge vision deployments fail not because of model architecture, but because real-world training data is structurally incomplete. Sampled data can’t cover combinatorial edge… “Why Edge Vision Models Keep
“How Qualcomm Is Making Computer Vision Accessible Across Edge Verticals,” a Presentation from Qualcomm Technologies, Inc.
Derrick Chang, Senior Product Manager at Qualcomm Technologies, Inc. presents “How Qualcomm Is Making Computer Vision Accessible Across Edge Verticals” at the May 2026 Embedded Vision Summit. Computer vision at the edge is no longer limited by algorithms; it is constrained by power, latency, system complexity and deployment friction across… “How Qualcomm Is Making Computer
