Generative AI is revolutionizing data and analytics, but its applications demand advanced data management capabilities to handle vast, diverse, and complex datasets that include images, video, audio, ...

Vector databases unlock the insights buried in complex data including documents, videos, images, audio files, workflows, and system-generated alerts. Here’s how. The world of data is rapidly changing ...

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Vector database startup Pinecone Systems Inc. today announced a new, high-performance deployment option for customers that need to support the most demanding enterprise use cases. It’s called ...

Startup Zilliz Inc. today debuted a new release of its flagship offering, a managed vector database called Zilliz Cloud that artificial intelligence models can use to hold information. Redwood Shores, ...

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 ...

Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...

With an emphasis on AI-first strategy and improving Google Cloud databases' capability to support GenAI applications, Google announced developments in the integration of generative AI with databases.

The emergence of vector databases and vector search for handling massive quantities of complex data have radically transformed the way AI is implemented and managed. As a specialized approach for ...

Timescale is looking to further advance its namesake open-source database platform with new AI capabilities announced today. Timescale was founded in 2017 as a time series database (TSDB) technology ...