Large Language Models as Classification Engines: Overkill, or Awesome?

Author(s): Katherine Munro

Originally published on Towards AI.

Why is it an odd choice? Why you should try it anyway. And how to go about it.

Have you ever wanted to build a trillion-parameter labelling machine? And by that I mean, would you use a Large Language Model to solve a classification problem?

The article discusses the unconventional use of Large Language Models (LLMs) as classification engines, explaining that while they are not naturally suited for classification tasks due to their complexity and unpredictability, they can still provide benefits like rapid prototyping and ease of use without needing extensive retraining. It includes various approaches to implement LLMs in classification, explores real-world applications like customer intent detection, and emphasizes the importance of balancing accuracy with the inherent challenges of using LLMs for such tasks. Examples from a telecommunications provider illustrate these concepts effectively.

Read the full blog for free on Medium.

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Published via Towards AI