Retrieval Augmented Generation (RAG) has taken the generative AI world by storm. By combining vector databases and large language models, RAG has become the de facto way to search and navigate enterprise data for generative AI.&nbsp;
Join Douwe Kiela, the inventor of retrieval augmentation, for a fireside chat with DataStax to discuss the origins of RAG, and where it is going. We'll cover specific advanced topics such as multimodal models and fine-tuning with RAG. Lastly, we'll get a sneak peak at some of the activities of Douwe's foundation model startup <a href="https://contextual.ai/">Contextual.ai</a>.
In a live fireside chat on Thursday, September 28 at 10 am CET, guest speaker from Contextual AI &mdash;Douwe Kiela, CEO/Co-Founder &mdash; will share how RAG and other Gen AI principles behind the company's startup success. We will explore Gen AI hot topics like:
<ul>
<li style="font-weight: 400;" aria-level="1">Where RAG came from and what&rsquo;s next</li>
<li style="font-weight: 400;" aria-level="1">Large Language Models (LLMs)</li>
<li style="font-weight: 400;" aria-level="1">Foundation models and the role they play at Contextual AI</li>
</ul>
Don't miss this opportunity to learn from Douwe and to explore the unlimited possibilities that RAG, LLMs and Gen AI can unlock for your organization.

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Where did Retrieval Augmented Generation (RAG) come from and where is it going?

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Alan Ho

Douwe Kiela

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Where did Retrieval Augmentation Generation come from and where is it going?

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Alan Ho

Douwe Kiela