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Image credit: Snapshot of the Talk

Learn the basics of secure and private AI techniques, including federated learning and secure multi-party computation. In this talk, Andrew Trask of OpenMined highlights the importance of privacy preserving machine learning, and how to use privacy-focused tools like PySyft. (This is a talk uploaded by the PyTorch community on youtube).

PyTorch

🔘 External talk pages: youtu.be/4zrU54VIK6k & youtu.be/4zrU54VIK6k

Short version

Long version (MIT Deep Learning Series)

Summary

“The mission of the OpenMined community is to create an accessible ecosystem of tools for private, secure, multi-owner governed AI. We do this by extending popular libraries like TensorFlow and PyTorch with advanced techniques in cryptography and private machine learning”. (Source: openmined.org)

Author

undefined Andrew Trask. Leader of @OpenMined, Senior Research Scientist at DeepMind, PhD Student at Oxford, Author of Grokking Deep Learning, Instructor at Udacity. (Source: github.com/iamtrask

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