The future of machine learning is decentralized - Alex Ingerman (Google)

With the advent of connected devices with computation and storage capabilities, it is now possible to run machine learning workflows entirely on-device. This talk will introduce federated learning and other technologies that enable devices to collaboratively and securely learn ML models, while retaining all data locally. Federated learning improves upon the traditional, fully centralized approaches by reducing the costs and risks related to sensitive data handling, working better in bandwidth and power-constrained environments, and providing a straightforward, effective mechanism for personalization at scale. It also puts users back in control of their data, while still enabling developers to build intelligent applications that leverage insights from that data. Federated learning is already used at-scale by Google - come to this talk to hear how!

Alex Ingerman is a senior product manager at Google, focused on Federated Learning. Before joining Google, he lead the product management team for Amazon Machine Learning. He joined Amazon in 2012, after working on products including web-scale search, content recommendation systems, immersive data exploration environments, and enterprise email and content servers. Alex holds a Bachelor of Science degree in Computer Science, and a Master of Science degree in Medical Engineering.