Data-as-Code: Securing the Future of AI Model Development


Posted on in Presentations

Today, data is a first-class input to AI-powered applications alongside code and configuration. However, many AI development practices are ad-hoc. To achieve end-to-end guarantees on lineage, integrity, and safety of models, one must adopt a Data-as-Code (DaC) approach. This session will explore the tenets of DaC from VCS to training to storage to serving and implementing.

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Participants
Bharath Chandrasekhar

Speaker

Senior Staff Software Engineer, Mandiant, Google Cloud

Anton Chuvakin

Speaker

Senior Staff Security Advisor, Google Cloud


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