Generative AI promises to be one of the most --&nbsp; if not THE most -- significant technology revolutions. <a href="https://www.datastax.com/guides/what-is-a-vector-database">Vector databases</a> &ldquo;speak the language of&rdquo; <a href="https://www.datastax.com/guides/what-is-a-large-language-model">Large Language Models</a> (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.&nbsp;
Read this industry analyst report to learn:
<ul>
<li style="font-weight: 400;" aria-level="1">Why vector search and vector stores (databases) are critical for generative AI applications</li>
<li style="font-weight: 400;" aria-level="1">How to create vectors, store vector embeddings and perform a vector search</li>
<li style="font-weight: 400;" aria-level="1">Decoding the AI Pipeline: Retrieval Augmented Generation (RAG)</li>
<li style="font-weight: 400;" aria-level="1">Evaluation criteria for choosing a vector databases</li>
<li style="font-weight: 400;" aria-level="1">How DataStax&rsquo;s Astra DB vector database stacks up</li>
</ul>
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Get an overview how how vector search powers RAG and GenAI apps.

What is a Vector Database?

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