Onehouse Inc., a company that sells a data lakehouse based on Apache Hudi as a managed service, today said it has launched a vector embedding generator to automate embedding pipelines as a part of its ...

Dutch artificial intelligence database startup Weaviate B.V. is looking to streamline the data vectorization process with a new feature that automatically transforms unstructured information into ...

Vector embeddings are the backbone of modern enterprise AI, powering everything from retrieval-augmented generation (RAG) to semantic search. But a new study from Google DeepMind reveals a fundamental ...

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 ...

A new open-source framework called PageIndex solves one of the old problems of retrieval-augmented generation (RAG): handling very long documents. The classic RAG workflow (chunk documents, calculate ...

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 ...

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 ...

Have you ever searched for something online, only to feel frustrated when the results didn’t quite match what you had in mind? Maybe you were looking for an image similar to one you had, or trying to ...