Software

“Key Requirements to Successfully Implement Generative AI in Edge Devices—Optimized Mapping to the Enhanced NPX6 Neural Processing Unit IP,” a Presentation from Synopsys

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Gordon Cooper, Principal Product Manager at Synopsys, presents the “Key Requirements to Successfully Implement Generative AI in Edge Devices—Optimized Mapping to the Enhanced NPX6 Neural Processing Unit IP” tutorial at the May 2025 Embedded Vision Summit. In this talk, Cooper discusses emerging trends in generative AI for edge devices and… “Key Requirements to Successfully Implement […]

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Upcoming Webinar Explores SLAM Optimization for Autonomous Robots

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On July 10, 2025 at 8:00 am PT (11:00 am ET), Alliance Member company eInfochips will deliver the free webinar “GPU-Accelerated Real-Time SLAM Optimization for Autonomous Robots.” From the event page: Optimizing execution time for long-term and large-scale SLAM algorithms is essential for real-time deployments on edge compute platforms. Higher throughput of SLAM output provides

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AI and Computer Vision Insights at CVPR 2025

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This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Our papers, demos, workshops and tutorial continue our leadership in generative AI and learning systems At Qualcomm AI Research, we are advancing AI to make its core capabilities — perception, reasoning and action — ubiquitous across devices.

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“Bridging the Gap: Streamlining the Process of Deploying AI onto Processors,” a Presentation from SqueezeBits

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Taesu Kim, Chief Technology Officer at SqueezeBits, presents the “Bridging the Gap: Streamlining the Process of Deploying AI onto Processors” tutorial at the May 2025 Embedded Vision Summit. Large language models (LLMs) often demand hand-coded conversion scripts for deployment on each distinct processor-specific software stack—a process that’s time-consuming and prone… “Bridging the Gap: Streamlining the

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“From Enterprise to Makers: Driving Vision AI Innovation at the Extreme Edge,” a Presentation from Sony Semiconductor Solutions

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Amir Servi, Edge Deep Learning Product Manager at Sony Semiconductor Solutions, presents the “From Enterprise to Makers: Driving Vision AI Innovation at the Extreme Edge” tutorial at the May 2025 Embedded Vision Summit. Sony’s unique integrated sensor-processor technology is enabling ultra-efficient intelligence directly at the image source, transforming vision AI… “From Enterprise to Makers: Driving

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AI Helps Locate Dangerous Fishing Nets Lost at Sea

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This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Conservationists have launched a new AI tool that can sift through petabytes of underwater imaging from anywhere in the world to identify signs of abandoned or lost fishing nets—so-called ghost nets. Each year, around 2% of the

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The SHD Group Releases New Edge AI Processor and Ecosystem Report

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Now available for free download from Alliance Member company The SHD Group is their latest market report, Edge AI Market Analysis: Applications, Processors and Ecosystem Guide, developed in partnership with the Edge AI and Vision Alliance. The report provides a detailed exploration of the rapidly evolving edge AI landscape, covering critical insights on emerging applications,

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What Is Agentic AI? A Complete Guide to the Future of Autonomous Intelligence

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This blog post was originally published at Geisel Software’s website. It is reprinted here with the permission of Geisel Software. What is agentic AI? It refers to intelligent systems that can autonomously set goals, make decisions, and execute tasks without constant human input. It marks a significant shift from reactive chatbots to proactive, mission-oriented AI

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SplitQuant: Layer Splitting for Low-bit Neural Network Quantization for Edge AI Devices

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This blog post was originally published at Nota AI’s website. It is reprinted here with the permission of Nota AI. This study proposes an AI model preprocessing method for improved quantization accuracies on edge AI devices which do not support advanced quantization methods due to their limitations. By splitting layers based on parameter clustering, the

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“State-space Models vs. Transformers for Ultra-low-power Edge AI,” a Presentation from BrainChip

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Tony Lewis, Chief Technology Officer at BrainChip, presents the “State-space Models vs. Transformers for Ultra-low-power Edge AI” tutorial at the May 2025 Embedded Vision Summit. At the embedded edge, choices of language model architectures have profound implications on the ability to meet demanding performance, latency and energy efficiency requirements. In… “State-space Models vs. Transformers for

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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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