Generative AI promises to be one of the most -- if not THE most -- significant technology revolutions. Vector databases “speak the language of” Large Language Models (LLMs) and are at the center of the rapid adoption of and innovation around generative AI. With a vector database, users can take large amounts of enterprise data, contextualize it, process it, and enable it to be searched with meaning by LLMs.
Read this industry analyst report to learn:
- Why vector search and vector stores (databases) are critical for generative AI applications
- How to create vectors, store vector embeddings and perform a vector search
- Decoding the AI Pipeline: Retrieval Augmented Generation (RAG)
- Evaluation criteria for choosing a vector databases
- How DataStax’s Astra DB vector database stacks up