Felix Liao
Director of Product Management, APAC
Large Language Models (LLMs) and Generative AI are transformative but pose enterprise adoption challenges due to their lack of inherent business-specific knowledge.
The solution is the Retrieval Augment Generation (RAG) architecture, which provides LLMs with contextual knowledge. However, implementing RAG requires an effective data management foundation. This underscores the need for organizations to improve their data management strategies and leverage a logical data layer such as the Denodo Platform, in preparation for an AI-led future.
Three key takeaways participants will gain from the session:
- Large Language Models (LLMs) and Generative AI hold significant potential for transforming industries, but their lack of inherent business-specific knowledge poses challenges.
- Retrieval Augment Generation (RAG) architecture is a solution that safely and effectively provides these AI models with the necessary context, improving their understanding and operation within an enterprise.
- Implementing RAG and other advanced AI applications necessitates a robust, flexible data management foundation, underlining the importance of a flexible data fabric layer.
We will conclude this session with an open Q&A.
Join us in this illuminating discussion on the future of AI with Denodo.
