Keeping data confidential with fully homomorphic encryption. [Research Saturday]
Guest Dr. Rosario Cammarota from Intel Labs joins us to discuss confidential computing. Confidential computing provides a secure platform for multiple parties to combine, analyze and learn from sensitive data without exposing their data or machine learning algorithms to the other party. This technique goes by several names — multiparty computing, federated learning and privacy-preserving analytics, among them. Confidential computing can enable this type of collaboration while preserving privacy and regulatory compliance.
The research and supporting documents can be found here:
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A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
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