Federated learning in production (part 1)

Federated learning in production (part 1)

Author: Practical AI LLC May 30, 2025 Duration: 44:38

In this first of a two part series of episodes on federated learning, we dive into the evolving world of federated learning and distributed AI frameworks with Patrick Foley from Intel. We explore how frameworks like OpenFL and Flower are enabling secure, collaborative model training across silos, especially in sensitive fields like healthcare. The conversation touches on real-world use cases, the challenges of distributed ML/AI experiments, and why privacy-preserving techniques may become essential for deploying AI to production.

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There's a lot of noise out there about artificial intelligence, but cutting through the hype to find what's genuinely useful can be a challenge. That's the space where Practical AI operates. Hosted by the team at Practical AI LLC, this technology podcast moves beyond abstract theory to explore how AI, machine learning, and large language models are actually being applied right now. Each episode features unscripted conversations with a diverse mix of experts, developers, business leaders, and curious minds. You'll hear tangible discussions about implementing machine learning systems, the realities of MLOps, the evolution of neural networks, and the practical implications of breakthroughs in deep learning and GANs. The dialogue is grounded in real-world scenarios, focusing on how these technologies solve problems, drive productivity, and create value in accessible ways. Whether you're a professional building models, a business person integrating AI tools, or an enthusiast eager to understand the landscape, this podcast offers a clear, conversational entry point. It’s about making sense of a complex field through the lens of practical application, demystifying the concepts that are shaping our world without losing sight of how they work on the ground.
Author: Language: en-us Episodes: 100

Practical AI
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