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23. December 2024
Nvidia and DataStax Revolutionize Generative AI with Groundbreaking Storage Solution
The tech giants have teamed up to deliver a game-changing innovation that drastically reduces storage requirements for companies deploying generative AI systems, while enabling faster and more accurate information retrieval across multiple languages. The new Nvidia NeMo Retriever microservices, integrated with DataStax’s AI platform, has slashed data storage volume by an astonishing 35 times compared to traditional approaches.
Enterprise data is projected to reach over 20 zettabytes by 2027, with the current unstructured data already reaching 11 zettabytes – roughly equivalent to 800,000 copies of the Library of Congress. Today’s enterprise unstructured data is a massive challenge, with 83% being audio and video, and 50% unstructured. Significantly reducing these storage costs while enabling companies to effectively embed and retrieve information becomes a game changer.
Nvidia’s NeMo Retriever technology delivers a staggering 35x improvement in data storage efficiency, as illustrated in a comparison of raw text storage, baseline vector embeddings, and reduced embedding dimensions. This breakthrough underpins the scalability of generative AI across enterprise applications. Wikimedia Foundation has already seen transformative results from using the integrated solution, reducing processing time for 10 million Wikipedia entries from 30 days to under three days.
The system handles real-time updates across hundreds of thousands of entries being edited daily by 24,000 global volunteers. The partnership addresses a critical challenge facing enterprises: how to make their vast stores of private data accessible to AI systems without exposing sensitive information to external language models. Data security meets AI accessibility with the new solution, providing a much-needed balance between making data available for AI and protecting sensitive information.
Financial services firms are leading the charge in adopting this technology, despite regulatory constraints. “I’ve been blown away by how far ahead financial services firms are now,” said Chet Kapoor, CEO of DataStax. Nvidia plans to expand the technology’s capabilities to handle more complex document formats. “We’re seeing great results with multimodal PDF processing – understanding tables, graphs, charts, and images and how they relate across pages,” Kari Briski, VP of product management for AI at Nvidia, revealed.
For enterprises drowning in unstructured data while trying to deploy AI responsibly, the new offering provides a path to make their information assets AI-ready without compromising security or breaking the bank on storage costs. The solution is available immediately through the Nvidia API catalog with a 90-day free trial license.