In this episode, Anthony Alcaraz (Chief Product Officer) and Andreas Welsch discuss supercharging your Retrieval Augmented Generation (RAG) application with a knowledge graph. Anthony shares his experience expanding Generative AI applications and large language models and provides valuable tips for listeners looking to get even more relevant results from their AI applications.

Key topics:
- Identify shortcomings of Retrieval Augmented Generation (RAG)
- Describe a knowledge graph and its purpose
- Learn how to build a knowledge graph
- Clarify when to use a knowledge graph

Listen to the full episode to hear how you can:
- Provide context between data sources with a knowledge graph
- Gather and prepare qualitative data to build your knowledge graph and AI model on
- Treat knowledge graphs as one concept among others in your AI strategy
- Start with the business problem and identify the best data sources and methods for solving it

Watch this episode on YouTube:
https://youtu.be/OSj08YBdQrg

Questions or suggestions? Send me a Text Message.

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Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.

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