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 ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The traditional way for a database to answer a query is with a list of ...

Kinetica, the real-time GPU-accelerated database for analytics and generative AI, unveiled at NVIDIA GTC its real-time vector similarity search engine that can ingest vector embeddings 5X faster than ...

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Vector databases have emerged to become an integral component of many AI applications. However, as AI applications continue to grow, vector databases are presented with more complicated use cases.

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 ...

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 ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Real time database vendor Rockset is ...

I recently wrote a Finextra piece entitled 3 GenAI Use Cases for Capital Markets; The Power of the Vector. In it, I discussed the increasing importance of the so-called vector database and vectors ...