NVIDIA

How NVIDIA Jetson AGX Orin Helps Unlock the Power of Surround-view Camera Solutions

This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Autonomous vehicles, such as warehouse robots, rely on precise maneuvering. NVIDIA Jetson AGX Orin™-powered surround-view cameras provide a perfectly synchronized solution, allowing these robots to move freely within designated areas without requiring intensive manual intervention. […]

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Streamlining AI Inference Performance and Deployment with NVIDIA TensorRT-LLM Chunked Prefill

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. In this blog post, we take a closer look at chunked prefill, a feature of NVIDIA TensorRT-LLM that increases GPU utilization and simplifies the deployment experience for developers. This builds on our previous post discussing how advanced

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Microchip to Accelerate Real-time Edge AI with NVIDIA Holoscan

PolarFire® FPGA Ethernet Sensor Bridge provides low-power multi-sensor bridging to NVIDIA edge AI platforms CHANDLER, Ariz., November 14, 2024 — To enable developers building artificial intelligence (AI)-driven sensor processing systems, Microchip Technology (Nasdaq: MCHP) has released its PolarFire® FPGA Ethernet Sensor Bridge that works with the NVIDIA Holoscan sensor processing platform. PolarFire FPGAs enable multi-protocol

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How to Accelerate Larger LLMs Locally on RTX With LM Studio

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. GPU offloading makes massive models accessible on local RTX AI PCs and workstations. Editor’s note: This post is part of the AI Decoded series, which demystifies AI by making the technology more accessible, and showcases new hardware,

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Give AI a Look: Any Industry Can Now Search and Summarize Vast Volumes of Visual Data

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Accenture, Dell Technologies and Lenovo are among the companies tapping a new NVIDIA AI Blueprint to develop visual AI agents that can boost productivity, optimize processes and create safer spaces. Enterprises and public sector organizations around the

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Optimizing the CV Pipeline in Automotive Vehicle Development Using the PVA Engine

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. In the field of automotive vehicle software development, more large-scale AI models are being integrated into autonomous vehicles. The models range from vision AI models to end-to-end AI models for autonomous driving.  Now the demand for computing

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Flux and Furious: New Image Generation Model Runs Fastest on RTX AI PCs and Workstations

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Black Forest Labs’ latest models generate high-quality images and are highly performant on NVIDIA RTX GPUs. Editor’s note: This post is part of the AI Decoded series, which demystifies AI by making the technology more accessible, and

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Orchestrating Innovation at Scale with NVIDIA Maxine and Texel

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. The NVIDIA Maxine AI developer platform is a suite of NVIDIA NIM microservices, cloud-accelerated microservices, and SDKs that offer state-of-the-art features for enhancing real-time video and audio. NVIDIA partners use Maxine features to create better virtual interaction

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The Rise of AI Drives a Ninefold Surge in Liquid Cooling Technology

AI servers, driven by Nvidia’s GB200 superchip, have experienced significant growth. The cutting-edge B200 chip, due to its high thermal design power, requires direct-to-chip cooling. Supermicro announced that it had shipped over 2000 direct-liquid-cooled AI server racks by the end of August 2024, and it has expanded its manufacturing capacity to 5000 racks per month.

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Accelerating LLMs with llama.cpp on NVIDIA RTX Systems

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. The NVIDIA RTX AI for Windows PCs platform offers a thriving ecosystem of thousands of open-source models for application developers to leverage and integrate into Windows applications. Notably, llama.cpp is one popular tool, with over 65K GitHub

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