NVIDIA and DataStax Revolutionize Multilingual AI with NeMo Retriever Microservices

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NVIDIA launches NeMo Retriever microservices for multilingual generative AI, partnering with DataStax to dramatically improve data processing efficiency and language understanding across industries.

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NVIDIA Introduces NeMo Retriever for Multilingual AI

NVIDIA has unveiled its latest innovation in the field of artificial intelligence: NeMo Retriever microservices. This groundbreaking technology is designed to enhance multilingual generative AI capabilities, addressing the growing need for language-inclusive AI solutions in global enterprises 1.

Key Features and Capabilities

NeMo Retriever offers several critical functionalities:

  1. Multilingual Information Retrieval: The system can search, process, and retrieve knowledge across multiple languages, enabling AI to deliver more accurate and globally relevant outputs 1.

  2. Cross-Format Understanding: NeMo Retriever can comprehend information from various formats, including documents, making it versatile for diverse enterprise needs 1.

  3. Vector Embedding: The technology transforms data into AI-ready formats, significantly speeding up the processing of large datasets 2.

  4. Evaluation and Reranking: NeMo Retriever examines and ranks retrieved information based on relevance to queries, enhancing accuracy 2.

Partnership with DataStax and Impact on Wikimedia

NVIDIA has partnered with DataStax to implement NeMo Retriever in vectorizing Wikipedia content. This collaboration has yielded impressive results:

  • Processing time for 10 million Wikidata entries reduced from 30 days to under three days 1.
  • Real-time updates for hundreds of thousands of entries edited daily by thousands of contributors 1.
  • 35 times reduction in data storage volume compared to traditional approaches 3.

Industry Adoption and Applications

Several leading companies are already adopting NeMo Retriever microservices:

  • DataStax, Cohesity, Cloudera, Nutanix, SAP, VAST Data, and WEKA are integrating the technology to connect custom models to diverse data sources 1.
  • Financial services firms, including Commonwealth Bank of Australia and Capital One, are early adopters despite regulatory constraints 3.

Future Developments

NVIDIA is working on expanding NeMo Retriever's capabilities:

  • Multimodal data processing, including images, PDFs, and video 2.
  • Advanced PDF processing to understand and relate tables, graphs, charts, and images across pages 3.

Availability and Access

Developers can access NeMo Retriever microservices through the NVIDIA API catalog or with a no-cost, 90-day NVIDIA AI Enterprise developer license 1. This offering provides enterprises with a path to make their information assets AI-ready without compromising security or incurring excessive storage costs 3.

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