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 ...

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 ...

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 ...

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 ...

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 ...

News flash: Vector databases and vector searches are no longer a differentiation. Yes, how fast times change as what was cool just six months ago is suddenly table stakes! What is cool is a unified ...

Organizations that are using TimescaleDB to store and query their time-series data may be interested to know that they can use the database to store and query vectors for GenAI applications, too.

Patrick Walsh is the cofounder and CEO of IronCore Labs, the data security encryption platform for software companies and AI. The proliferation of generally intelligent AI models is turning machine ...