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Xilinx Adds Advanced Machine Learning Capabilities

Xilinx has announced a range of new and advanced machine learning (ML) capabilities for Xilinx devices targeted at the professional audio/video (Pro AV) and broadcast markets.

xilinx-2Additionally, Xilinx unveiled the industry’s first demonstration of a programmable HDMI 2.1 implementation on its 7nm Versal devices.

Xilinx is showcasing these capabilities and more at Integrated Systems Europe (ISE) 2020, taking place this week in Amsterdam. These and other highly adaptable Xilinx solutions for the Pro AV and broadcast markets are designed to help customers reduce costs and future proof investments while keeping pace with new usage models and evolving industry standards.

Newly available ML capabilities for Xilinx Pro AV and broadcast platforms include region-of-interest encoding, intelligent digital signage, automatic object tracking and window cropping, and speech recognition. Customers can now take advantage of these ML capabilities on Xilinx devices, including the already highly integrated Zynq UltraScale+ MPSoC platform, for AI edge processing.

The combination of real-time audio and video processing, AV connectivity interfaces, codecs, IP networking, CPU, and GPU into an adaptable and scalable single-chip solution can provide users with significant space, power, and cost savings.

“Machine learning is a rapidly developing technology that is stimulating new usage models in Pro AV and broadcast,” said Ramesh Iyer, director of Pro AV & Broadcast at Xilinx. “Adding ML into Xilinx’s adaptable platforms provides a highly integrated AV processor that delivers proven support for 8K video, AV-over-IP, and compression, and now adds advanced capabilities for monetizing analytics, improving workflow efficiency and enhancing usability. Ultimately, these integrated ML features will allow companies to increase innovation, differentiate themselves, and accelerate time-to-market.”

Pro AV market customers can apply the new ML capabilities across many applications and workloads. Key examples, include:

Region-of-Interest Encoding – detect faces and features using ML and the Zynq UltraScale+ MPSoC integrated H.264/H.265 codec to keep video quality high in those areas and apply higher compression for backgrounds. This reduces the overall bitrate and saves significant costs in live streaming.

Intelligent Digital Signage – using ML models for gender, age and gesture detection to present targeted interactive advertising in digital signage. The result is a higher return on investment for advertisers as well as monetizable behaviour metrics.

Automated Object Tracking and Window Cropping – output multiple HD windows from a single 4K camera using ML. This is particularly useful when providing switchable content at live events and in control rooms.

Speech Recognition – automatically output text from speech, which is ideal for automating the transcription of meeting notes and language translation in conferencing and collaboration.

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Nitisha Dubey

I am a Journalist with a post graduate degree in Journalism & Mass Communication. I love reading non-fiction books, exploring different destinations and varieties of cuisines. Biographies and historical movies are few favourites.

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