Zephyrnet Logo

Xilinx AI Webinars

Date:

Interested to find out more about how Xilinx is enabling AI in both Cloud and Edge applications? 

Here are three on-demand webinars you can view right now:

Developer Webinar: Integrating AI into Your Accelerated Cloud Applications (Watch Now)

In this webinar, you will get a detailed walk-through of CNN acceleration on the recently released Xilinx ML suite, which is conveniently deployed on the Amazon EC2 cloud. Register now to learn how to use this cloud-based software stack to evaluate, develop, and deploy machine learning capabilities into your accelerated applications on the AWS cloud.

Accelerating Predictive Maintenance with Python and Neural Network-based Edge AI (Watch Now)

Subtle changes in performance or behavior of critical assets in factories, hospitals, and other environments can be identified by machines much earlier than a human. Xilinx powered systems can incorporate intelligence to maximize productivity and lower downtime by applying predictive maintenance. Xilinx’s Python and Neural Network-based Edge AI Solutions simplify the implementation of hardware accelerated predictive maintenance to continuously monitor assets, analyze data, and intelligently plan service for these systems. In this webinar, you will see how this is done on an Industrial Motor and go beyond!

Python Powered Edge Analytics & Machine Learning for Electric Drives (Watch Now)

This webinar will introduce the foundational concepts motivating the use of Xilinx Zynq SoCs in Electric Drives applications. Showing examples of how PYNQ can enable software engineers and data scientists to easily gain valuable on-chip, real-time insights from data generated by the motor, with or without cloud connectivity. The key differentiation with PYNQ lies in the configurable hardware pre-processing of sensor data leading to the most efficient use of the application software.

Source: https://forums.xilinx.com/t5/AI-and-Machine-Learning-Blog/Xilinx-AI-Webinars/ba-p/966689

spot_img

Latest Intelligence

spot_img