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.

Did you know that over 80% of the data generated today is unstructured? Traditional databases often fall short in managing this type of data efficiently. That’s where vector databases come into play.

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 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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When Aquant Inc. was looking to build its platform — an artificial intelligence service that supports field technicians and agents teams with an AI-powered copilot to provide personalized ...

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Vector databases, a relatively new type of database that can store and ...