Most vector search systems struggle with a basic problem: how to break complex documents into searchable pieces. The typical approach is to split text into fixed size chunks of 200 to 500 tokens, this ...

When designing search systems, the decision to use keyword-based search, vector-based search, or a hybrid approach can significantly impact performance, relevance, and user satisfaction. Each method ...

Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable. Suppose you wanted to ...

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What is vector search and how is it transforming the search experience? Edo Liberty, CEO of Pinecone and former head of Amazon's AI lab, explains. We’ve been talking with search industry pros and ...

SAN FRANCISCO--(BUSINESS WIRE)--Algolia today launched Algolia NeuralSearch™, a next-generation vector and keyword search in a single API with powerful, end-to-end AI processing every query. Algolia ...

The dramatic advances in generational AI—chatGPT in particular—have motivated almost all technology companies to find an AI story that can break through the heavily AI-oriented technology news feeds.

Vector database offers on-prem, cloud-native, or SaaS deployment, leading performance, a rich set of integrations and language drivers, and a dizzying array of optimization options. Efficient ...