Bio: Jem is an Arm fellow and general manager of Arm’s Machine Learning business, focusing on machine learning and artificial intelligence solutions. He was previously GM and vice president of technology for the Media Processing, and Imaging and Vision, Groups, where he set the future technology roadmaps and undertook technological investigations for several acquisitions. Based in Cambridge, Jem was previously a member of Arm’s Architecture Review Board and holds four patents in the fields of CPU and GPU design.

Keynote Title: Enabling Machine Learning to Explode with Open Standards and Collaboration

Keynote Abstract: It’s impossible to become an expert in machine learning(ML). Many “domain-specific” technologies are driven by a handful of use cases, but machine learning is so pervasive in applications that it’s unachievable to master it. To add to this complexity, it’s the ML “wild west” with competing approaches, multiple de facto standards and several standards efforts producing many different ‘versions’ of neural networks and operators to support. Arm believes that the way through is to develop open standards and collaborate on common-core technologies which enable developers to move faster. Connecting them to the right platform in a consistent way, and allowing them to focus on delivering their solution rather than fighting with practicalities. With the collaboration of ML framework developers, hardware developers and the Arm platform, a consistent software platform and developer experience across a huge range of devices can be developed to unlock experts in each and every field that machine learning touches.