A 'picker' gathers items at Amazon's Fulfilment Centre in Peterborough, central England, on November 28, 2013. 'Cyber Monday' which falls this year on Monday December 2, 2013, is expected to be the ...

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 ...

Despite the aggressive cost claims and dramatic scale improvements, AWS is positioning S3 Vectors as a complementary storage ...

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 ...

Pembroke, MA - September 15: A bumblebee gathers nectar from a Mexican sunflower. (Photo by John Tlumacki/The Boston Globe via Getty Images) Databases are changing. They’re changing because they are ...

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 ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Data platform vendor DataStax is entering the vector database space, ...

This expansion is fueled by the rapid adoption of AI, LLMs, and multimodal applications that require high-performance vector search, scalable indexing, and real-time retrieval. By offering, the ...

Vector databases explained through speed vs velocity: why AI needs vectors, not rows and columns, to manage context, similarity, and next-gen RAG workloads, dqdeeptech ...

Built by the team behind Amazon SageMaker. Having attracted investment by Wing Venture Capital, with Wing's Founding Partner and early Snowflake investor, Peter Wagner, joining startup Pinecone's ...