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Retrieval Augmented Generation (RAG) AI:
In this episode, host Evan Reid sits down with data strategy expert Heather Harris, PhD and developer Mohammed Afnan Waseem for an in-depth conversation on the opportunities and challenges of deploying Retrieval-Augmented Generation (RAG) AI systems. The discussion begins with an exploration of data strategy, focusing on the importance of understanding proprietary data, questions around data ownership, and how RAG systems retrieve and apply information in real time. The panel then breaks down system design fundamentals, highlighting key components such as embeddings and vectorization, while also addressing infrastructure considerations using cloud platforms like AWS and Azure. They dive into the risks associated with using proprietary data in AI, including concerns over intellectual property, data security, and potential legal implications. The conversation also touches on policy considerations, including the development of AI governance frameworks.
5
1010 ratings
Retrieval Augmented Generation (RAG) AI:
In this episode, host Evan Reid sits down with data strategy expert Heather Harris, PhD and developer Mohammed Afnan Waseem for an in-depth conversation on the opportunities and challenges of deploying Retrieval-Augmented Generation (RAG) AI systems. The discussion begins with an exploration of data strategy, focusing on the importance of understanding proprietary data, questions around data ownership, and how RAG systems retrieve and apply information in real time. The panel then breaks down system design fundamentals, highlighting key components such as embeddings and vectorization, while also addressing infrastructure considerations using cloud platforms like AWS and Azure. They dive into the risks associated with using proprietary data in AI, including concerns over intellectual property, data security, and potential legal implications. The conversation also touches on policy considerations, including the development of AI governance frameworks.
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