April 19, 2022

How Federated Machine Learning Powers Privacy

How Federated Machine Learning Powers Privacy

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 comp...

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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.

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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.


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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.

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David Bauer Jr.Profile Photo

David Bauer Jr.


Dr. Bauer heads research and product development in Artificial Intelligence and Deep Learning at BOSS AI, which uses AI to provide context for data.
As a computer science professional, Dr. Bauer has dedicated his efforts to solving hard problems using Distributed Computing. He has pioneered codes that have executed on 2 million CPUs, and developed the first Cloud and Big Data platform Certified & Accredited for use in the entirety of the Federal Government (way back in 2009).
Among some of the major challenges he has tackled include applying machine learning to Synthetic Biology to create Chemical Warfare sensors; developing the first MULTI-INT data fusion platform using Big Data and Ai for the U.S. Intelligence Community; developing the first distributed computing platform to demonstrate super-linear scalability up to 2 million CPUs at Lawrence Livermore; and developing the first report for the GAO and DHS National Communications System that combined analysis of the effects of pandemic influenza on Internet communications, the US Economy and Banking System, and Financial Markets. Dr. Bauer was a leader in developing areas for study in Exa-scale computing at DARPA and has worked on several unique problems in the IC that have worked to keep the United States free from those that would harm us.
Dr. Bauer is the most excited when presented with an impossible problem to solve. No problem is impossible or intractable! Trained in distributed systems, he feels there are very few problems that cannot be solved leveraging large-scale technologies including Big Data, Cloud Computing, Virtualization, and of course, Parallel Programming. Distributed computing will continue to digitally transform our world and I hope to continue contributing to that process for as long as possible.
Dr. Bauer has been programming since 1982 when he received my first Vic20, and his first love in this area is crafting solution architectures that solve (or approximate) solutions for impossible problems.