The current world is data-driven, with information being continuously collected and processed at increasing levels. Much of this data is sensitive — e.g. Personally Identifiable Information (PII) or ...
As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines. By Daniel Fusch Neel Somani, a ...
Homomorphic encryption is a transformative cryptographic method that permits computations to be executed directly on encrypted data without the need for decryption. This capability not only guarantees ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...
The latest trends and issues around the use of open source software in the enterprise. Alibaba Group’s global research initiative Alibaba DAMO Academy has made the source code of its latest federated ...
In the fourth and fifth publications we move from synthetic data to efficient privacy-preserving computations. We start by studying the use of simulated data to optimise a privacy mechanism that makes ...
Data privacy regulations like GDPR, the CCPA and HIPAA present a challenge to training AI systems on sensitive data, like financial transactions, patient health records and user device logs.
In the 19th century, the barons of American industries rose to prominence by leveraging their hold on tangible resources like oil and steel. Today, corporate titans seek to attain even greater heights ...
Ant Group recently announced that its “privacy-preserving” Computation Framework becomes open source, aiming “to make the technologies more accessible to global developers and speed up the Framework’s ...
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