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NetApp's Novus addresses critical metadata bottlenecks in AI infrastructure by decoupling metadata management from stored data to enable independent scaling for large GPU clusters. The platform integrates an AI Data Engine that automates data discovery, classification, and vectorization, significantly reducing the engineering time required to prepare enterprise datasets for models and agents. This unified storage approach aims to resolve fragmentation issues that often hinder enterprises from realizing returns on their AI investments.

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NetApp’s Novus tackles metadata bottlenecks in AI data infrastructure

SiliconANGLEOctober 5, 20263 min read

AI data infrastructure must support growing GPU clusters while making enterprise data usable for models and agents. NetApp Inc. is tying intelligent data infrastructure to production AI through a unified approach to storage and data management. Fragmented data and governance designed around manually applied policies can prevent enterprises from realizing returns on AI investments, according […] The post NetApp’s Novus tackles metadata bottlenecks in AI data infrastructure appeared first on SiliconANGLE.

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