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Edge AI and Vision Insights is our bi-weekly newsletter, delivering the latest technology, applications, markets, and trends in edge AI and vision right to your inbox. To receive Insights, please register via the “Subscribe to the Edge AI and Vision Insights Newsletter” section in the right column of this page.

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Most Recent Issues

Edge AI and Vision Insights: July 8, 2026

  LETTER FROM THE EDITOR Dear Colleague, This week we’re looking at how edge AI and vision development is becoming more productive, more scalable and more accessible across real-world applications. Two upcoming webinars explore important pieces of this evolution: using edge-first coding agents to accelerate development for real devices, and making computer vision easier to deploy across a broad range of edge verticals. Also in this issue, we highlight presentations on bringing advanced vision-language-action models to embedded systems, optimizing NPUs for transformer workloads and scaling edge AI from prototypes to production deployments. Many of our readers are eager to share their expertise with peers, and I’m pleased to announce that the Call for Presentation Proposals for the 2027 Embedded Vision Summit is now open! The 2027 Summit will take place February 2-4 in San Francisco, California. We would love to see your ideas—from physical AI case studies to efficient edge AI techniques to the latest advances in vision-language models. Check out the 2027 topics list on the Call for Proposals page for inspiration and to ...
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Edge AI and Vision Insights: June 24, 2026

  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. Also in this issue, we look at why memory is becoming a central bottleneck for edge AI and how robotics developers are moving from benchmarks toward fleet-scale deployment. We also have two upcoming webinars focused on especially timely challenges: using synthetic data to overcome gaps in real-world training sets, and using generative AI to help port computer vision applications to OpenCV 5. On Tuesday, August 11, we’ll present a webinar on synthetic data in collaboration with Synetic AI. 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 cases, forcing perpetual retraining cycles that break embedded deployment, explainability requirements and silicon viability. In this session, David ...
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Edge AI and Vision Insights: June 10, 2026

  LETTER FROM THE EDITOR Dear Colleague, This week’s featured presentations focus on practical ways to accelerate edge AI development—from choosing programmable FPGA-based accelerators and designing efficient computer vision systems for tightly constrained far-edge devices to using AI coding agents safely and effectively in real embedded development workflows. Efinix and Lattice Semiconductor examine hardware and model-design strategies for meeting demanding cost, power, latency, memory and I/O constraints. Ambarella and Boston.AI explore how AI-assisted software development can help teams build trustworthy edge systems and navigate major platform transitions such as OpenCV 5. But before we get to those topics, I want to alert you to an interesting event. Alliance partner KOTRA invites you to explore cutting-edge innovations at Physical AI Superconnect 2026 on June 24 in Mountain View, California. Engage with nearly 40 Korean companies showcasing component- and system-level advancements in manufacturing and service robots, autonomous driving and more. It’s a great opportunity to connect with innovative companies and new technologies. Learn more and register here. Erik Peters Director of Ecosystem and Community Engagement, Edge AI ...
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Edge AI and Vision Insights: October 1, 2025

October 1, 2025

OPTIMIZING DEEP LEARNING MODEL EFFICIENCY Quantization Techniques for Efficient Deployment of Large Language Models: A Comprehensive Review The deployment of large language models (LLMs) in resource-constrained environments is challenging due

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Edge AI and Vision Insights: June 25, 2025

June 25, 2025

LANGUAGE MODEL OPTIMIZATIONS FOR EDGE PROCESSORS Bridging the Gap: Streamlining the Process of Deploying AI onto Processors Large language models often demand hand-coded conversion scripts for deployment on each distinct

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Edge AI and Vision Insights: October 1, 2025

October 1, 2025

OPTIMIZING DEEP LEARNING MODEL EFFICIENCY Quantization Techniques for Efficient Deployment of Large Language Models: A Comprehensive Review The deployment of large language models (LLMs) in resource-constrained environments is challenging due

Read More +

Edge AI and Vision Insights: June 25, 2025

June 25, 2025

LANGUAGE MODEL OPTIMIZATIONS FOR EDGE PROCESSORS Bridging the Gap: Streamlining the Process of Deploying AI onto Processors Large language models often demand hand-coded conversion scripts for deployment on each distinct

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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