Processors

Speeding Up Deep Learning Inference Using TensorFlow, ONNX, and TensorRT

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Starting with TensorRT 7.0,  the Universal Framework Format (UFF) is being deprecated. In this post, you learn how to deploy TensorFlow trained deep learning models using the new TensorFlow-ONNX-TensorRT workflow. Figure 1 shows the high-level workflow of TensorRT. […]

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Application Processor Unit (APU) Quarterly Market Monitor

Application processor: All-in-one solution for the computing challenges of the next decade MARKET DYNAMICS: 2019 APU market closed with total revenue of $31B. Seasonally weak Q1-20 expected to remain above $7B even as COVID-19 stresses the supply chain. Cost & ASP declines at ~20% per year through 2021; slowing to ~10% per year for 2022+.

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Maximize CPU Inference Performance with Improved Threads and Memory Management in Intel Distribution of OpenVINO Toolkit

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. The popularity of convolutional neural network (CNN) models and the ubiquity of CPUs means that better inference performance can deliver significant gains to a larger number of users than ever before. As multi-core processors become the norm,

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“Market Analysis on SoCs for Imaging, Vision and Deep Learning in Automotive and Mobile Markets,” a Presentation from Yole Développement

John Lorenz, Market and Technology Analyst for Computing and Software at Yole Développement, delivers the presentation “Market Analysis on SoCs for Imaging, Vision and Deep Learning in Automotive and Mobile Markets” at the Edge AI and Vision Alliance’s March 2020 Vision Industry and Technology Forum. Lorenz presents Yole Développement’s latest analysis on the evolution of

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CEVA Announces DSP and Voice Neural Networks Integration with TensorFlow Lite for Microcontrollers

WhisPro™ speech recognition software for voice wake words and custom command models now available with open source TensorFlow Lite for Microcontrollers implementing machine learning at the edge TensorFlow Lite for Microcontrollers from Google is already optimized and available for CEVA-BX DSP cores, accelerating the use of low power AI in conversational and contextual awareness applications

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Ultra-Wide is Ultra-Hot, and a Lot of Work

Wide angle cameras are hot in smartphones, cars, VR and surveillance, for convenience, cost or safety. Turning wide-angle, high-res input into pleasing and usable high-resolution output in real-time depends on a holistic solution with special optics, dedicated hardware and customized software. Recent-release phones have three cameras, for the iPhone 11 a wide-angle lens, a telephoto

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Learning to Rank with XGBoost and GPU

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. XGBoost is a widely used machine learning library, which uses gradient boosting techniques to incrementally build a better model during the training phase by combining multiple weak models. Weak models are generated by computing the gradient descent using

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Streamline Your Intel Distribution of OpenVINO Toolkit Development with Deep Learning Workbench

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. Back in 2018, Intel launched the Intel® Distribution of OpenVINO™ toolkit. Since then, it’s been widely adopted by partners and developers to deploy AI-powered applications in various industries, from self-checkout kiosks to medical imaging to industrial robotics.

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“PyTorch Deep Learning Framework: Status and Directions,” a Presentation from Facebook

Joseph Spisak, Product Manager at Facebook, delivers the presentation “PyTorch Deep Learning Framework: Status and Directions” at the Embedded Vision Alliance’s December 2019 Vision Industry and Technology Forum. Spisak gives an update on the Torch deep learning framework and where it’s heading.

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“Current and Planned Standards for Computer Vision and Machine Learning,” a Presentation from the Khronos Group

Neil Trevett, President of the Khronos Group and Vice President of Developer Ecosystems at NVIDIA, delivers the presentation “Current and Planned Standards for Computer Vision and Machine Learning” at the Embedded Vision Alliance’s December 2019 Vision Industry and Technology Forum. Trevett shares updates on recent, current and planned Khronos standardization activities aimed at streamlining the

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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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