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 ...
BERLIN & NEW YORK, March 12, 2026--(BUSINESS WIRE)--Qdrant, the open-source vector search engine built in Rust for production workloads, today announced $50 million in Series B funding led by AVP, ...
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 ...
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 ...
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 ...
News flash: Vector databases and vector searches are no longer a differentiation. Yes, how fast times change as what was cool just six months ago is suddenly table stakes! What is cool is a unified ...
The latest trends in software development from the Computer Weekly Application Developer Network. Hazelcast has made sure it keeps its platform progression evolving in line with current major trends ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...
ScyllaDB today announced Vector Search for its DynamoDB-compatible API (Alternator). For the first time, developers building on the DynamoDB API can run high-performance vector similarity search ...
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