The AMD Kria SOM family helps tackle the processing challenges from the explosion of sensor data that is being produced at the edge. 

As embedded AI, video, and control applications explode, there is a growing need for heterogeneous processing to accelerate end-to-end compute within tight area and power constraints. Multi-chip processing solutions come with significant power, area, and complexity overhead; instead, designers need support for flexible, real-time preprocessing, efficient AI inference, and high-performance postprocessing on a single device.

Learn how Xilinx is helping Telefónica design and develop next-generation wireless radio networks using O-RAN.

Check out Xilinx's automotive news from CES 2019.

Check out highlights from Victor Peng's keynote address at the 3rd annual Xilinx Developer Forum (XDF) in 2019.

The most critical AI video analytics applications are the ones that protect human health, preserve human life, and secure property, and complex applications like that need deterministic low latency performance. Not only that, but their complexity can be extremely hardware intensive, which can challenge organizational budgets.

AI models and deep learning are key technologies that are used to gain insight on ... Aupera appliances enable higher performance, lower latency and reduced bandwidth ... Want to learn more?