The Wikimedia Foundation, the nonprofit that hosts Wikipedia and other Wikimedia projects, today announced the launch of its "Knowledge is Human.

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Nvidia and DataStax launched new technology today that dramatically 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, cuts data storage volume by 35 times compared to traditional approaches — a crucial capability as enterprise data is projected to reach more than 20 zettabytes by 2027.“Today’s enterprise unstructured data is at 11 zettabytes, roughly equal to 800,000 copies of the Library of Congress, and 83% of that is unstructured with 50% being audio and video,” said Kari Briski, VP of product management for AI at Nvidia, in an interview with VentureBeat. “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 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. (Credit: Nvidia)The technology is already proving transformative for Wikimedia Foundation, which used the integrated solution to reduce processing time for 10 million Wikipedia entries from 30 days to under three days

By partnering with the Wikimedia Foundation to conduct the first-ever audit of Wikipedia under the DSA, Holistic AI is also helping VLOPs assess and mitigate the risks of online platforms and implement best practices that prioritize innovation, safety, and accountability.