Retrieval Augmented Generation and the Evolution of Data Science Roles
Overview
Harpreet Sahota discusses the evolving roles within data science and the intriguing potential of Retrieval Augmented Generation (RAG). Harpreet shares insights from his journey transitioning from traditional data science to deep learning and developer advocacy, emphasizing the importance of following one's curiosity. They discuss how RAG can enhance large language models by incorporating real-time, personalized data, thereby making AI tools more applicable and efficient across various industries. The episode also covers Harpreet's initiatives in creating educational resources and community-driven research, aiming to push the boundaries of AI and deep learning further. For anyone interested in the future of AI and its integration into everyday tasks, this episode provides a deep dive into the technological advancements shaping the field.
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