<?xml-stylesheet type="text/xsl" href="https://community.cadence.com/cfs-file/__key/system/syndication/rss.xsl" media="screen"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" xmlns:wfw="http://wellformedweb.org/CommentAPI/"><channel><title>Common Tensilica Software Stack Delivers Best-In-Class Edge AI Performance</title><link>/cadence_blogs_8/b/artificial-intelligence/posts/common-tensilica-software-delivers-best-in-class-edge-ai-performance</link><description>Developing an agile software stack is important for successful AI deployment on the edge. We regularly encounter new machine learning models created from multiple AI frameworks that leverage the latest primitives and state-of-the-art ML model topolog</description><dc:language>en-US</dc:language><generator>Telligent Community 12</generator></channel></rss>