How Federated Machine Learning Powers Privacy

Futurized - thought leadership on the future - A podcast by Trond Arne Undheim

In episode 151 of the podcast, the topic is: How Federated Machine Learning Powers Privacy. Our guest is Dave Bauer, CTO, BOSS AI. In this conversation, we talk about what federated machine learning is and why care, noting its effects on distributed compute, edge clusters, privacy preserving features, and the emerging use cases. Futurized goes beneath the trends to track the underlying forces of disruption in tech, policy, business models, social dynamics and the environment. I’m your host, Trond Arne Undheim (@trondau), futurist, author, investor, and serial entrepreneur. Join me as I discuss the societal impact of deep tech such as AI, blockchain, IoT, nanotech, quantum, robotics, and synthetic biology, and tackle topics such as entrepreneurship, trends, or the future of work. On the show, I interview smart people with a soul: founders, authors, executives, and other thought leaders, or even the occasional celebrity. Futurized is a bi-weekly show, preparing YOU to think about how to deal with the next decade's disruption, so you can succeed and thrive no matter what happens. If you're new to the show, seek particular topics, or you are looking for a great way to tell your friends about the show, which we always appreciate, we've got the episode categories. Those are at Futurized.org/episodes. They are collections of your favorite episodes organized by topic, such as Entrepreneurship, Trends, Emerging Tech, or The Future of Work. That'll help new listeners get a taste of everything that we do here, starting with a topic they are familiar with, or want to go deeper in. The host of this podcast, Trond Arne Undheim, Ph.D is the author of Augmented Lean: A Human-Centric Framework for Managing Frontline Operations (co-authored with Natan Linder and published by Wiley in 2022), Health Tech: Rebooting Society's Software, Hardware and Mindset--published by Routledge in 2021, Future Tech: How to Capture Value from Disruptive industry Trends--published by Kogan Page in 2021, Pandemic Aftermath: how Coronavirus changes Global Society and Disruption Games: How to Thrive on Serial Failure (2020)--both published by Atmosphere Press in 2020, and Leadership From Below: How the Internet Generation Redefines the Workplace by Lulu Press in 2008. For an overview, go to Trond's Books at Trondundheim.com/books At this stage, Futurized is lucky enough to have several sponsors. To check them out, go to Sponsors | Futurized - thoughts on our emerging future. If you are interested in sponsoring the podcast, or to get an overview of other services provided by the host of this podcast, including how to book him for keynote speeches, please go to Store | Futurized - thoughts on our emerging future. We will consider all brands that have a demonstrably positive contribution to the future. Before you do anything else, make sure you are subscribed to our newsletter on Futurized.org, where you can find hundreds of episodes of conversations that matter to the future. I hope you can also leave a positive review on iTunes or in your favorite podcast player--it really matters to the future of this podcast. Thanks so much, let's begin. Trond's takeaway: The future outlook for Federated Machine Learning is that it takes a key role in facilitating supercompute, that it supports low/no-code development, becomes a lynchpin for safeguarding privacy, and ultimately, powers novel user experiences such as immersive graphics.   Thanks for listening. If you liked the show, subscribe at Futurized.org or in your preferred podcast player, and rate us with five stars. If you like this topic, you may enjoy other episodes of Futurized, such as episode 140, [When will Conversational AI get Real?], episode 69, [The Future of Quantum Security], or episode 30, [The Quest for Artificial General Intelligence]. Hopefully, you'll find something awesome in these or other episodes. If so, do let us know by messaging us, we would love to share your thoughts with other listeners.