Artificial intelligence (AI) processing rests on the use of vectorised data. In other words, AI turns real-world information into data that can be used to gain insight, searched for and manipulated.

Companies across every industry increasingly understand that making data-driven decisions is a necessity to compete now, in the next five years, in the next 20 and beyond. Data growth — unstructured ...

In today’s data-driven world, the exponential growth of unstructured data is a phenomenon that demands our attention. The rise of generative AI and large language models (LLMs) has added even more ...

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 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 ...

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 ...

Timescale Inc., the creator of a cloud time-series database that’s based on PostgreSQL, is looking to cater to artificial intelligence developers with the launch of its latest vector capabilities.

Rockset today unveiled new vector database capabilities, such as the addition of approximate nearest neighbor (ANN) search and native support for LlamaIndx and LangChain, that it says will help ...

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

HeatWave GenAI is 30X faster than Snowflake, 18X faster than Google BigQuery, and 15X faster than Databricks for vector processing With HeatWave GenAI, developers can create a vector store for ...