Processors

“Simplifying Portable Computer Vision with OpenVX 2.0,” a Presentation from AMD

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Kiriti Nagesh Gowda, Staff Engineer at AMD, presents the “Simplifying Portable Computer Vision with OpenVX 2.0” tutorial at the May 2025 Embedded Vision Summit. The Khronos OpenVX API offers a set of optimized primitives for low-level image processing, computer vision and neural network operators. It provides a simple method for… “Simplifying Portable Computer Vision with […]

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“Quantization Techniques for Efficient Deployment of Large Language Models: A Comprehensive Review,” a Presentation from AMD

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Dwith Chenna, MTS Product Engineer for AI Inference at AMD, presents the “Quantization Techniques for Efficient Deployment of Large Language Models: A Comprehensive Review” tutorial at the May 2025 Embedded Vision Summit. The deployment of large language models (LLMs) in resource-constrained environments is challenging due to the significant computational and… “Quantization Techniques for Efficient Deployment

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Learn to Optimize Stable Diffusion on Qualcomm Cloud AI 100

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This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Dive in to learn how we achieve a 1.4x latency decrease on Qualcomm Cloud AI 100 Ultra accelerators by applying an innovative DeepCache technique to text-to-image generation. What’s more, the throughput can be further improved by 3x

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Texas Instruments Demonstration of Edge AI Inference and Video Streaming Over Wi-Fi

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The demonstration shows how to use Texas Instruments’ AM6xA to capture live video, perform machine learning, and stream video over Wi-Fi. The video is encoded with H.264/H.265, and streamed via UDP over Wi-Fi using the CC33xx. At the receiver side, the video is decoded and displayed on a screen.  The receiver side could be a

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Machine Vision Defect Detection: Edge AI Processing with Texas Instruments AM6xA Arm-based Processors

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Texas Instruments’ portfolio of AM6xA Arm-based processors are designed to advance intelligence at the edge using high resolution camera support, an integrated image sensor processor and deep learning accelerator. This video demonstrates using AM62A to run a vision-based artificial intelligence model for defect detection for manufacturing applications. Watch the model test the produced units as

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“Introduction to Radar and Its Use for Machine Perception,” a Presentation from Cadence

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Amol Borkar, Product Marketing Director, and Vencatesh Subramanian, Design Engineering Architect, both of Cadence, co-present the “Introduction to Radar and Its Use for Machine Perception” tutorial at the May 2025 Embedded Vision Summit. Radar is a proven technology with a long history in various market segments and continues to plays an increasingly important role in

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BrainChip Launches Akida Cloud for Instant Access to Latest Akida Neuromorphic Technology

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Aligns with BrainChip’s long-term strategy to accelerate customer access to its innovations and reduce development cycles LAGUNA HILLS, Calif.–(BUSINESS WIRE)–BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based neuromorphic AI, today announced launch of the BrainChip Developer Akida Cloud, a new cloud-based access point

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Optimizing LLMs for Performance and Accuracy with Post-training Quantization

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This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Quantization is a core tool for developers aiming to improve inference performance with minimal overhead. It delivers significant gains in latency, throughput, and memory efficiency by reducing model precision in a controlled way—without requiring retraining. Today, most models

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Alif Semiconductor Demonstration of Face Detection and Driver Monitoring On a Battery, at the Edge

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Alexandra Kazerounian, Senior Product Marketing Manager at Alif Semiconductor, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Kazerounian demonstrates how AI/ML workloads can run directly on her company’s ultra-low-power Ensemble and Balletto 32-bit microcontrollers. Watch as the AI/ML AppKit runs real-time face detection using an

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OpenMV Demonstration of the OpenMV Cam N6 and AE3

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Kwabena Agyeman, president and co-founder of OpenMV, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Agyeman demonstrates the new OpenMV Cam N6 and AE3, which can run AI models in a form factor the size of an inch. The new OpenMV Cams can run on

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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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