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Explore the unconventional application of Large Language Models (LLMs) for classification tasks in this insightful conference talk from DSC EUROPE 24. Katherine Munro examines why LLMs—typically considered slow, random black boxes—seem counterintuitive for tasks demanding speed, accuracy, and interpretability. Despite these apparent limitations, discover the practical value LLMs bring to real-world classification scenarios. Learn about emerging architectures and techniques for integrating LLMs into classification systems, illustrated through a customer intent detection case study. Gain valuable insights from Katherine's experience building a next-generation conversational assistant at Switzerland's largest telecommunications provider, offering perspective on universal challenges and solutions in this evolving field.
