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Why Norway’s Environmental Commitment Reflects in Vespa.ai’s Values
Exploring how Vespa.ai exemplifies Norway's commitment to sustainability through efficient technology.
Vespa for Dummies
A beginner's guide to Vespa, exploring its role in information retrieval and its advantages for enterprise AI applications.
A Benchmark for Modernizing Elasticsearch with Vespa
Discover how Vespa outperforms Elasticsearch in query efficiency, scalability, and operational costs, making it a robust choice for modern eCommerce search solutions.
Visual RAG over PDFs with Vespa - A demo application in Python
This is a technical blog post on developing an end-to-end Visual RAG application powered by Vespa. It has link to a live demo application, and will walk you through why...
Navigating in the New AI-Driven E-commerce Landscape
This AI-driven ecommerce evolution is driven by consumer’s increasing demand for personalized experiences, real-time interactions, and seamless omnichannel integration.
Elasticsearch vs Vespa Performance Comparison
Detailed report of a comprehensive performance comparison between Vespa and Elasticsearch for an e-commerce search application.
How Generative AI Is Changing E-commerce
According to ESG, 41% of retail respondents in a 2024 survey are either already pursuing or planning to pursue AI-powered product recommendations.
Photo by
Catherine Kay Greenup
on
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Vector search beyond the database
The purpose of using vectors is to improve quality, but that takes much more than a similarity lookup. Search engines are built for that, databases are not.
Vespa Newsletter, October 2024
Advances in Vespa features and performance include Global significance models and Nearest Neighbor Search with multiple sparse tensor dimensions.
Vespa.ai: The “Sleeping Giant” Powering Next-Gen Search and Recommendations
Vespa has quietly led the way in search and recommendation systems, providing the backbone for some of today’s most advanced applications.
Deploying RAG at Scale: Key Questions for Vendors
Retrieval-augmented generation (RAG) has emerged as a vital technology for organizations embracing generative AI.
Announcing support for global significance models
A global significance model improves ranking for streaming search and ensures deterministic search results in multi-node deployments.
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