Learn why Google’s TurboQuant may mark a major shift in search, from indexing speed to AI-driven relevance and content discovery.

Google unveils TurboQuant, PolarQuant and more to cut LLM/vector search memory use, pressuring MU, WDC, STX & SNDK.

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...

Hosted search and discovery platform for enterprise Algolia Inc. today launched NeuralSearch, a vector and keyword search engine using a single application programming interface that provides ...

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 ...

For a long time, vector databases were a bit of a niche product, but because they are uniquely suited to provide context and long-term memory to large language models, everybody in the database space ...

Rockset, the leading search and analytics database built for the cloud, is announcing native support for hybrid search, redefining the potential of search and AI applications. Now, users can benefit ...

Artificial intelligence-driven search and discovery startup Marqo.ai said today it has closed on an A$8 million (about $5.2 million USD) seed funding round. The lead investor in the company, ...

Open-source vector database provider Qdrant has launched BM42, a vector-based hybrid search algorithm intended to provide more accurate and efficient retrieval for retrieval-augmented generation (RAG) ...

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Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More SingleStore is advancing its namesake database platform with a new ...