NVIDIA Ampere Architecture Comes to Jetson, Delivering up to 200 TOPS and 6x Performance Gain Tuesday, November 9, 2021—GTC—NVIDIA today introduced NVIDIA Jetson AGX Orin™, the world’s smallest, most powerful and energy-efficient AI supercomputer for robotics, autonomous machines, medical devices and other forms of embedded computing at the edge. Built on the NVIDIA Ampere architecture, […]
Capital One, Microsoft, Samsung Medison, Siemens Energy, Snap Among Industry Leaders Worldwide Using Platform Tuesday, November 9, 2021—GTC—NVIDIA today announced major updates to its AI inference platform, which is now being used by Capital One, Microsoft, Samsung Medison, Siemens Energy and Snap, among its 25,000+ customers. The updates include new capabilities in the open source
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. High-performance, energy-efficient AI compute is heightening autonomous vehicles’ detection capabilities. For autonomous vehicles, what’s on the surface matters. While humans are taught to avoid snap judgments, self-driving cars must be able to see, detect and act quickly
Ekaterina Sirazitdinova, Data Scientist at NVIDIA, presents the “Getting Started with Vision AI Model Training” tutorial at the May 2021 Embedded Vision Summit. In many modern vision and graphics applications, deep neural networks (DNNs) enable state-of-the-art performance for tasks like image classification, object detection and segmentation, quality enhancement and even new content generation. In this
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Neil Trevett, Vice President of Developer Ecosystems at NVIDIA and President of the Khronos Group, presents the “Khronos Group Standards: Powering the Future of Embedded Vision” tutorial at the May 2021 Embedded Vision Summit. Open standards play an important role in enabling interoperability for faster, easier deployment of vision-based systems. With advances in machine learning,
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Fueled by data, ML models are the mathematical engines of AI, expressions of algorithms that find patterns and make predictions faster than a human can. When you shop for a car, the first question is what model
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Barrie Mullins, Director of Technical Product Marketing at NVIDIA, presents the “Streamlining Development of Edge AI Applications” tutorial at the May 2021 Embedded Vision Summit. Edge AI provides benefits for cost, latency, privacy, and connectivity. Developing and deploying optimized, accurate and effect AI on edge-based systems is a time-consuming, challenging and complex process. In this
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7/28/21 – FRAMOS offers camera data transfer over a single coax cable using the GMSL2 protocol on the Jetson AGX Xavier platform. Camera developers utilizing the FRAMOS Sensor Module Ecosystem can integrate the highly flexible GMSL2 technology with image sensors producing up to 8MP resolution at 30fps over cable length of 15m. Developers benefit from
Evan Juras, Computer Vision Engineer at BDTI, and Braulio Ríos, Machine Learning Engineer at Tryolabs, co-present the “A Mask Detection Smart Camera Using the NVIDIA Jetson Nano: System Architecture and Developer Experience” tutorial at the May 2021 Embedded Vision Summit. MaskCam is a prototype reference design for a smart camera that counts the number of
Tuesday, July 20, 2021 – NVIDIA today launched TensorRT™ 8, the eighth generation of the company’s AI software, which slashes inference time in half for language queries — enabling developers to build the world’s best-performing search engines, ad recommendations and chatbots and offer them from the cloud to the edge. TensorRT 8’s optimizations deliver record-setting
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