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One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...

Overview: AutoML is transforming data science by automating data preparation, feature engineering, model selection, and deployment workflows across enterprises.

The reliance on public data — mostly web data — to train AI is holding back the AI field. That’s according to Daniel Beutel, a tech entrepreneur and researcher at the University of Cambridge, who ...

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.

The Hong Kong Applied Science and Technology Research Institute (ASTRI) joins forces with tech-embracing companies to leverage a privacy-preserving technology, called “Federated Learning”, to develop ...