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How FPGA-Based Frame Grabbers Are Powering Next-Gen Multi-Camera Systems

This article was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. FPGA-based frame grabbers are redefining multi-camera vision by enabling synchronized aggregation of up to eight GMSL streams for autonomous driving, robotics, and industrial automation. They overcome bandwidth and latency limits of USB and Ethernet by using PCIe […]

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December 17, 2025 Edge AI and Vision Alliance Member Briefing Presentations

The PDF files linked to below are the presentations from the December 17, 2025 Edge AI and Vision Alliance Member Briefing sessions. Please be aware that these materials are for Alliance Member company internal use only. December 17, 2025 Edge AI and Vision Alliance Member Briefing (Alliance) A recording of… December 17, 2025 Edge AI

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97% Smaller, Just as Smart: Scaling Down Networks with Structured Pruning

This article was originally published at Analog Devices’ website. It is reprinted here with the permission of Analog Devices. Why Smaller Models Matter Shrinking AI models isn’t just a nice-to-have—it’s a necessity for bringing powerful, real-time intelligence to edge devices. Whether it’s smartphones, wearables, or embedded systems, these platforms operate with strict memory, compute, and

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December 2025 Edge AI and Vision Innovation Forum Presentation Videos

Below you’ll find the privately published (i.e. appropriate only for viewing by Alliance Member company representatives) videos from the Alliance’s December 2025 Edge AI and Vision Innovation Forum. They are: The Introduction from Jeff Bier of the Edge AI and Vision Alliance Member company introduction presentations from TekStart, and Infineon… December 2025 Edge AI and

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AI On: 3 Ways to Bring Agentic AI to Computer Vision Applications

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Learn how to integrate vision language models into video analytics applications, from AI-powered search to fully automated video analysis. Today’s computer vision systems excel at identifying what happens in physical spaces and processes, but lack the abilities to explain the

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NVIDIA Debuts Nemotron 3 Family of Open Models

News Summary: The Nemotron 3 family of open models — in Nano, Super and Ultra sizes — introduces the most efficient family of open models with leading accuracy for building agentic AI applications. Nemotron 3 Nano delivers 4x higher throughput than Nemotron 2 Nano and delivers the most tokens per second for multi-agent systems at scale through a

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Better Than Real? What an Apple-Orchard Benchmark Really Says About Synthetic Data for Vision AI

If you work on edge AI or computer vision, you’ve probably run into the same wall over and over: The model architecture is fine. The deployment hardware is (barely) ok. But the data is killing you—too narrow, too noisy, too expensive to expand. That’s true whether you’re counting apples, spotting defects on a production line,

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Arm at NeurIPS 2025: How AI Research is Shaping the Future of Intelligent Computing

This blog post was originally published at Arm’s website. It is reprinted here with the permission of Arm. NeurIPS 2025 provided Arm with a unique opportunity to share the latest technical trends and insights with the global AI research community. NeurIPS is one of the world’s leading AI research conferences, acting as a thriving global hub for

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The Architecture Shift Powering Next-Gen Industrial AI

This blog post was originally published at Arm’s website. It is reprinted here with the permission of Arm. How Arm is powering the shift to flexible AI-ready, energy-efficient compute at the “Industrial Edge.” Industrial automation is undergoing a foundational shift. From industrial PC to edge gateways and smart sensors, compute needs at the edge are changing fast. AI is moving

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What is a Dust Denoising Filter in TOF Camera, and How Does it Remove Noise Artifacts in Vision Systems?

This article was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Time-of-Flight (ToF) cameras with IR sensors are susceptible to performance variations caused by environmental dust. This dust can create ‘dust noise’ in the output depth map, directly impacting camera accuracy and, consequently, the reliability of critical

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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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