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AI Needs More Than a Vector Database
An AI database is a multipurpose platform that manages both structured and unstructured data and applies AI models to various data formats.
Scaling ColPali to billions of PDFs with Vespa
Scaling Vision-Driven Document Retrieval with ColPali to large collections.
Parsing Through the Summer: A Tale of Schemas, Syntax, and Shenanigans
A tale of two interns who dove into the world of Vespa schemas, developing a language server.
Vespa Newsletter, August 2024
Advances in Vespa features and performance include new pyvespa and Vespa CLI features for queries, feeding, and deployment, shared match-phase heap, Chinese tokenization with Jieba, and new ranking framework features....
Beyond Text: The Rise of Vision-Driven Document Retrieval for RAG
Imagine a world where search engines see documents with human-like vision.
Vespa Terminology for Elasticsearch, OpenSearch or Solr People
Glossary of Vespa concepts, translated for engineers familiar with Lucene search engines: Elasticsearch, OpenSearch or Solr
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Small but Mighty: Using Answer.ai's ColBERT embedding model in Vespa
Using Answer.ai's ColBERT-small model for efficient and effective passage search
A New Bot: Dawn of a Vespa-Powered Slack Renaissance - A Summer Internship Story
Discover how we harnessed the power of Vespa.ai to build an evolving Slackbot that learns and adapts with every interaction!
Customer Engagement: Where the Generative AI Rubber Hits the Road
Exploring the challenges and potential of generative AI in e-commerce, focusing on customer engagement, search accuracy, and scalability.
Achieving AI at Scale Without Breaking the Bank in Financial Services
When implementing AI solutions in Financial Services, selecting a platform that maximizes efficiency, scalability, and performance is critical.
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David Travis
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PDF Retrieval with Vision Language Models
Connecting the ColPali model with Vespa for complex document format retrieval.
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Pau Sayrol
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Adaptive In-Context Learning 🤝 Vespa - part one
Adaptive In-Context Learning (ICL) with Vespa to retrieve context-sensitive examples
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