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 ...

Vector databases store, index, filter, and search embeddings so applications can retrieve items by similarity at operational scale. This guide explains the mechanism, trade-offs, evaluation, and ...

Vector databases don’t just store your data. They find the most meaningful connections within it, driving insights and decisions at scale. A vector database is just like any other database in that it ...

Vector databases have moved from a niche component of generative AI infrastructure to standard tooling across data-intensive industries. The technology now supports a range of enterprise applications ...

When you start learning about RAG, you encounter the term "vector database" quite early on.Create embeddings. Search for similar text. Pass the search results to an LLM.If you are just following a ...

Vector databases are making a resurgence as generative AI hype sweeps across every industry. Organizations with developed graph and relational databases may question if they need to add another ...

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, ...

Generative AI has received a lot of attention already this year in the tech world and beyond. Whether it's ChatGPT’s prose or Stable Diffusion’s art, 2022 provided an insight into the potential for AI ...

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 ...

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.