(Online Event) How to make machine learning at the edge work
June 11 @ 9:00 am - 12:00 pm
Join Stacey Higginbotham on June 11 from 9 am – 12 pm PDT for a virtual event for anyone who wants to develop a good understanding of what the edge is and how to take data and put it to good use, both from an industrial/enterprise perspective and consumer. They will touch on technical and business considerations while learning about compelling use cases from a variety of industries.
Register here: https://hopin.to/events/machine-learning-at-the-edge
Which Edge and Why (9-10 am PDT / 12-1 pm EDT)
Everyone has their own version of the edge. In this panel, we figure out how to define your edge, and explain what to consider when designing algorithms and equipment to run those algorithms on. We’ll also talk about challenges associated with the edge whether that edge is a field in Nebraska, a factory in Texas, or a firefighter’s pack in Massachusetts.
- Julian Sanchez, Director of Precision Agriculture at John Deere
- Karen Panetta, Dean of Graduate Education for the School of Engineering at Tufts University and IEEE Fellow
- Peter Zornio, CTO at Emerson Automation Solutions
How Shell Uses Computing at the Edge (10-11 am PDT / 1-2 pm EDT)
Shell has a lot of uses for machine learning at the edge, but deploying machine learning at scale across hundreds of thousands of nodes is still too difficult.
- Dan Jeavons, General Manager – Data Science at Shell
Making Money at the Outer Edge (11 am-12 pm PDT / 2-3 pm EDT)
Companies are buying software and gear to help them process data at the edge under the hope that they can make money, increase efficiencies, or predict failures. But at the outer edge, the computing can get expensive and the business models can prove elusive. Our panel of experts talks about how to think about investing in the edge while still generating returns.
- Rob Martens, SVP and Chief Innovation and Design Officer at Allegion
- Simon Crosby, CTO at Swim.ai
- Jason Shepherd, VP of Ecosystem at Zededa and LF Edge member