But since each vector is a high-dimensional float array, performing brute-force similarity comparisons across a large dataset can become prohibitively expensive, which is where vector indexing comes ...

As artificial intelligence reshapes marketing technology, vector search has emerged as a critical capability for 2025 data strategies. For marketing leaders, understanding how this technology ...

TL;DR Key Takeaways : Vector databases store and retrieve unstructured data (e.g., images, text, audio) using vector embeddings, allowing semantic search and bridging the “semantic gap ...

Hazelcast has made sure it keeps its platform progression evolving in line with current major trends and now introduced vector search. As TechTarget reminds us, vector search (sometimes referred ...

This pure vector-based hybrid search combines the best of both to achieve better results at lower costs in the realm of RAG. This will help users excel in the unfolding AI-centric world. Shifting ...

Scott Anderson, Couchbase’s senior vice president of product management and business operations, said vector search will enhance the results of each query its database handles.

Langford: I've been killing trees for twenty-five years. At Berkeley, back in the 20's. On the Japs at Iwo Jima. But I never brought one back from the grave before. I did, Becky. Momma's gonna ...

The market for vector search capabilities has become very competitive in 2023. Vectors, which are numerical representations of data, play a crucial role in fuelling large language models (LLMs).

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 ...