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Teradata's new capabilities focus on securing enterprise AI by integrating privacy controls directly with data management to prevent re-identification risks inherent in model training and inference. The inclusion of post-quantum security features like TLS 1.3 hybrid-key exchange specifically addresses emerging quantum-era threats, aligning infrastructure readiness with the evolving computational landscape. This product update underscores the critical shift toward protecting sensitive datasets as a foundational requirement for scalable AI deployment rather than an afterthought.

Surse care acoperăGDELT, arXiv, Quantum Zeitgeist, TechCrunch

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Teradata Introduces New Privacy, Security, and Resiliency Capabilities as AI Forces Change in Enterprise Data Protection

GDELT20 octombrie 20267 min de cititArticolul și perspectiva sunt în engleză.

, /PRNewswire/ -- Teradata (NYSE: TDC) today announced new privacy, security, and resiliency capabilities designed to address one of the defining challenges of enterprise AI: how sensitive data is protected, who and what can access it, and whether it remains available and recoverable when something goes wrong. Teradata addresses all three through an integrated approach that reduces raw identity exposure, enforces protection closer to the data, and keeps the intelligence powering AI available and recoverable. In practice, that means protecting the intelligence behind AI without diminishing what makes it valuable. Post-quantum security and readiness: strengthens protection against emerging quantum-era threats through Anonomatic PII Vault® and TLS 1.3 hybrid-key exchange for data in transit Why It Matters NowAs AI becomes mission-critical, it expands both the value and the vulnerability of enterprise data. Sensitive…

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