How ML, LLMs, AI, and KCS Work Together in Support

In this session, our speakers, Taranjeet Singh, and Lynette Ledoux delve into the dynamic landscape of machine learning, artificial intelligence, and large language models within the context of Knowledge-Centered Service. They emphasize the foundational role of Supervised Learning, an older sibling of Generative AI, as a powerful tool in labeling and decision-making processes. This session spotlights the practical applications of Supervised Learning in the Solve Loop, focusing on content findability, automated tagging for consistent content taxonomy, and identification of the Voice of the Customer issues. The Evolve loop is explored, showcasing automation in the Content Standard Checklist, Knowledge Domain Analysis, and Process Adherence Review for enhanced efficiency in knowledge workflows. Furthermore, the speakers engage in a thought-provoking discussion on the future possibilities in AI, touching on the implications of Artificial General Intelligence (AGI) and its potential impact on Knowledge-Centered Service. Key Takeaways Use Cases of Supervised Learning wrt to KCS GenAI Applications for Solve Loop GenAI Applications for Evolve Loop Future of GenAI and KCS