OpenFL: A Federated Learning Project to Power (and Secure) Your Projects
summary
OpenFL is a Python 3 framework for federated learning that actually ships: a pip package, containers, workspace/plan files and an integrated certificate authority, used by Intel and UPenn to train tumor‑detection models across over 71 medical institutions without centralizing patient data. It supports PyTorch/TensorFlow, offers narrow APIs for data scientists, and can run model aggregation inside Trusted Execution Environments (Intel SGX) so weights are encrypted in transit and while processed; demos and production cases show iterative federated rounds and improved accuracy.
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chapters (11)
- 0:00OpenFL and federated learning
- 3:15Federated learning data challenges
- 5:43OpenFL framework pillars
- 7:50Security risks in federated learning
- 10:23Securing data in transit
- 11:26Live demo of OpenFL
- 17:48OpenFL certificate authority
- 24:22OpenFL healthcare and NASA use cases
- 26:14Call to action and community
- 28:04Q&A: Horizontal vs vertical FL
- 30:14Q&A: OpenFL vs other FL frameworks
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