NVIDIA

Lattice Semiconductor Demonstration of NVIDIA Holoscan-compatible Cameras from Valued Partners

Jacob Mercado, Applications Engineer at Lattice Semiconductor, demonstrates the company’s latest edge AI and vision technologies and products at the 2025 Embedded Vision Summit. Specifically, Mercado demonstrates Holoscan camera solutions from ecosystem partner vendors Leopard Imaging and e-con Systems, designed with Lattice FPGAs for use with NVIDIA Orin AGX or IGX platforms. Holoscan is enabled […]

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Best-in-class Multimodal RAG: How the Llama 3.2 NeMo Retriever Embedding Model Boosts Pipeline Accuracy

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Data goes far beyond text—it is inherently multimodal, encompassing images, video, audio, and more, often in complex and unstructured formats. While the common method is to convert PDFs, scanned images, slides, and other documents into text, it

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Introducing NVFP4 for Efficient and Accurate Low-precision Inference

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. To get the most out of AI, optimizations are critical. When developers think about optimizing AI models for inference, model compression techniques—such as quantization, distillation, and pruning—typically come to mind. The most common of the three, without

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Simplifying Vision AI Development with Renesas AI Model Deployer Powered by NVIDIA TAO

This blog post was originally published at Renesas’ website. It is reprinted here with the permission of Renesas. Edge AI is no longer a futuristic idea—it’s an essential technology driving today’s smart devices across industries, from industrial automation to consumer IoT applications. But building AI applications at the edge still comes with challenges: complexity with

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R²D²: Building AI-based 3D Robot Perception and Mapping with NVIDIA Research

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Robots must perceive and interpret their 3D environments to act safely and effectively. This is especially critical for tasks such as autonomous navigation, object manipulation, and teleoperation in unstructured or unfamiliar spaces. Advances in robotic perception increasingly

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NVIDIA Holoscan Sensor Bridge Empowers Developers with Real-time Data Processing

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. In the rapidly evolving robotics and edge AI landscape, the ability to efficiently process and transfer sensor data is crucial. Many edge applications are moving away from single-sensor fixed-function solutions and in favor of diverse sensor arrays.

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AI Helps Locate Dangerous Fishing Nets Lost at Sea

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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AI Blueprint for Video Search and Summarization Now Available to Deploy Video Analytics AI Agents Across Industries

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. The age of video analytics AI agents is here. Video is one of the defining features of the modern digital landscape, accounting for over 50% of all global data traffic. Dominant in media and increasingly important for

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R²D²: Unlocking Robotic Assembly and Contact Rich Manipulation with NVIDIA Research

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. This edition of NVIDIA Robotics Research and Development Digest (R2D2) explores several contact-rich manipulation workflows for robotic assembly tasks from NVIDIA Research and how they can address key challenges with fixed automation, such as robustness, adaptability, and

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NVIDIA Unveils NVLink Fusion for Industry to Build Semi-custom AI Infrastructure With NVIDIA Partner Ecosystem

MediaTek, Marvell, Alchip Technologies, Astera Labs, Synopsys and Cadence to Create Custom AI Silicon With NVIDIA NVLink Ecosystem Fujitsu and Qualcomm Each Plan to Build Custom CPUs Coupled With NVIDIA GPUs, NVLink Scale-Up and Spectrum-X Scale-Out Technologies May 18, 2025—COMPUTEX—NVIDIA today unveiled NVIDIA NVLink Fusion™ — new silicon that lets industries build semi-custom AI infrastructure with the vast ecosystem

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