UPGRADE YOUR BROWSER

We have detected your current browser version is not the latest one. Xilinx.com uses the latest web technologies to bring you the best online experience possible. Please upgrade to a Xilinx.com supported browser:Chrome, Firefox, Internet Explorer 11, Safari. Thank you!

EETimes’ Junko Yoshida with some expert help analyzes this week’s Xilinx reVISION announcement

by Xilinx Employee ‎03-15-2017 01:25 PM - edited ‎03-22-2017 07:20 AM (597 Views)

 

Image3.jpgThis week, EETimes’ Junko Yoshida published an article titled “Xilinx AI Engine Steers New Course” that gathers some comments from industry experts and from Xilinx with respect to Monday’s reVISION stack announcement. To recap, the Xilinx reVISION stack is a comprehensive suite of industry-standard resources for developing advanced embedded-vision systems based on machine learning and machine inference.

 

(See “Xilinx reVISION stack pushes machine learning for vision-guided applications all the way to the edge.”)

 

As Xilinx Senior Vice President of Corporate Strategy Steve Glaser tells Yoshida, “Xilinx designed the stack to ‘enable a much broader set of software and systems engineers, with little or no hardware design expertise to develop, intelligent vision guided systems easier and faster.’

 

Yoshida continues:

 

While talking to customers who have already begun developing machine-learning technologies, Xilinx identified ‘8 bit and below fixed point precision’ as the key to significantly improve efficiency in machine-learning inference systems.

 

 

Yoshida also interviewed Karl Freund, Senior Analyst for HPC and Deep Learning at Moor Insights & Strategy, who said:

 

Artificial Intelligence remains in its infancy, and rapid change is the only constant.” In this circumstance, Xilinx seeks “to ease the programming burden to enable designers to accelerate their applications as they experiment and deploy the best solutions as rapidly as possible in a highly competitive industry.

 

 

She also quotes Loring Wirbel, a Senior Analyst at The Linley group, who said:

 

What’s interesting in Xilinx's software offering, [is that] this builds upon the original stack for cloud-based unsupervised inference, Reconfigurable Acceleration Stack, and expands inference capabilities to the network edge and embedded applications. One might say they took a backward approach versus the rest of the industry. But I see machine-learning product developers going a variety of directions in trained and inference subsystems. At this point, there's no right way or wrong way.

 

 

There’s a lot more information in the EETimes article, so you might want to take a look for yourself.

 

 

 

Labels
About the Author
  • Be sure to join the Xilinx LinkedIn group to get an update for every new Xcell Daily post! ******************** Steve Leibson is the Director of Strategic Marketing and Business Planning at Xilinx. He started as a system design engineer at HP in the early days of desktop computing, then switched to EDA at Cadnetix, and subsequently became a technical editor for EDN Magazine. He's served as Editor in Chief of EDN Magazine, Embedded Developers Journal, and Microprocessor Report. He has extensive experience in computing, microprocessors, microcontrollers, embedded systems design, design IP, EDA, and programmable logic.