AI tooling has taken enormous leaps forward, but it has largely left privacy behind. Companies building AI systems on private data need to know how to keep the data safe while still being able to employ these new tools.
In this webinar, we discuss modern AI systems and how to secure them. Plus, we explain the role of vector embeddings and how to protect embeddings with encryption-in-use.
We focused on four main areas in this webinar:
- How data flows through AI systems
- Where the data presents risks
- How the data is useful (such as preventing hallucinations)
- How to protect vector embeddings
- About the presenter:
Additional resources:
- Security of AI explainer ironcorelabs.c...
- Sign up for early access to encryption for vector databases with Cloaked AI ironcorelabs.c...
Негізгі бет How to Protect Sensitive Data in Generative AI Systems
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