AMD

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AMD Unleashes Ultimate PC Gaming Platform with Worldwide Availability of AMD Radeon RX 5700 Series Graphics Cards and AMD Ryzen 3000 Series Desktop Processors

AMD, News /

Introducing world’s first PCIe® 4.0 ready desktop CPUs and GPUs, designed to push the limits of gamers, enthusiasts, and content creators SANTA CLARA, Calif. – 07/07/2019 – Today, AMD (NASDAQ: AMD) announced the global availability of its new leadership PC gaming platform based on AMD Radeon™ RX 5700 series graphics cards and 3rd Gen AMD […]

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Xilinx Hits Milestone with First Customer Shipments of Versal ACAP

AMD, News /

Built on 7nm process technology, Versal is the industry’s first adaptive compute acceleration platform SAN JOSE, Calif., June 18, 2019 – Xilinx, Inc. (NASDAQ: XLNX), the leader in adaptive and intelligent computing, today announced that it has shipped Versal™ AI Core series and Versal Prime series devices to multiple tier one customers through the company’s

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2019 Vision Product of the Year Award Winner Showcase: Xilinx (Cloud Solutions)

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Xilinx's AI Platform is the 2019 Vision Product of the Year Award Winner in the Cloud Solutions category. Xilinx’s AI Platform provides a comprehensive set of software and IP to enable hardware accelerated AI inference applications. AI vision applications, which rely on convolutional neural networks, are a major target for the Xilinx AI Platform. The

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AMD Expands Embedded Product Family, Adds Design Wins and Customers, with New Ryzen Embedded R1000

AMD, News /

The AMD Ryzen™ Embedded R1000 SoC provides a new class of performance for the embedded industry with 3X performance per watt vs. previous AMD R-Series SoC1 and 4X performance per dollar compared to the competition2 TAIPEI, Taiwan – 04/16/2019 – At the Taiwan Embedded Forum, AMD (NASDAQ: AMD) announced the Ryzen™ embedded product family is

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2018 Vision Product of the Year Award Winner Showcase: Xilinx (Cloud Technologies)

AMD, Vision Product of the Year Awards /

Xilinx's Machine Learning Suite is the 2018 Vision Product of the Year Award Winner in the Cloud Technologies category. The Xilinx Machine Learning Suite provides tools for accelerating vision applications in the cloud. The key innovation of the Xilinx Machine Learning Suite is that it enables cloud users of machine learning inference to get an

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“Bad Data, Bad Network, or: How to Create the Right Dataset for Your Application,” a Presentation from AMD

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Mike Schmit, Director of Software Engineering for computer vision and machine learning at AMD, presents the “Bad Data, Bad Network, or: How to Create the Right Dataset for Your Application” tutorial at the May 2018 Embedded Vision Summit. When training deep neural networks, having the right training data is key. In this talk, Schmit explores

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“From Feature Engineering to Network Engineering,” a Presentation from ShatterLine Labs and AMD

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Auro Tripathy, Founding Principal at ShatterLine Labs (representing AMD), presents the “From Feature Engineering to Network Engineering” tutorial at the May 2018 Embedded Vision Summit. The availability of large labeled image datasets is tilting the balance in favor of “network engineering”instead of “feature engineering”. Hand-designed features dominated recognition tasks in the past, but now features

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“Leveraging Edge and Cloud for Visual Intelligence Solutions,” a Presentation from Xilinx

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Salil Raje, Senior Vice President in the Software and IP Products Group at Xilinx, presents the “Leveraging Edge and Cloud for Visual Intelligence Solutions” tutorial at the May 2018 Embedded Vision Summit. For many computer vision systems, a critical decision is whether to implement vision processing at the edge or in the cloud. In a

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“Achieving 15 TOPS/s Equivalent Performance in Less Than 10 W Using Neural Network Pruning,” a Presentation from Xilinx

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Nick Ni, Director of Product Marketing for AI and Edge Computing at Xilinx, presents the “Achieving 15 TOPS/s Equivalent Performance in Less Than 10 W Using Neural Network Pruning on Xilinx Zynq” tutorial at the May 2018 Embedded Vision Summit. Machine learning algorithms, such as convolution neural networks (CNNs), are fast becoming a critical part

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“Exploiting Reduced Precision for Machine Learning on FPGAs,” a Presentation from Xilinx

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Kees Vissers, Distinguished Engineer at Xilinx, presents the “Exploiting Reduced Precision for Machine Learning on FPGAs” tutorial at the May 2018 Embedded Vision Summit. Machine learning algorithms such as convolutional neural networks have become essential for embedded vision. Their implementation using floating-point computation requires significant compute and memory resources. Research over the last two years

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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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Berkeley Design Technology, Inc.
PO Box #4446
Walnut Creek, CA 94596

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Phone: +1 (925) 954-1411
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