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 ...
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 ...
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 ...
Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...
One of the key components of Microsoft’s Copilot Runtime edge AI development platform for Windows is a new vector search technology, DiskANN (Disk Accelerated Nearest Neighbors). Building on a ...
ScyllaDB today announced the general availability of its new Vector Search capability, which is integrated into ScyllaDB X Cloud. This high-performance vector search supports the industry’s largest ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this episode, Thomas Betts chats with ...
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 ...
ScyllaDB Vector Search is built on ScyllaDB’s shard-per-core architecture with a Rust-based extension that leverages the USearch approximate-nearest-neighbor (ANN) search library. The architecture ...
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