Honda: 2 years of ml vs 1 month of prompting - heres what we learned
12 days ago
- #warranty-analytics
- #machine-learning
- #prompt-engineering
- Major automakers face costly recalls, prompting the creation of an analytics department to categorize warranty claims.
- Traditional SQL queries struggle with modern warranty claim semantics, leading to misclassification and inefficiency.
- A 2023 initiative to automate warranty classification using supervised models faced challenges in data collection, preprocessing, and deployment.
- Large language models (LLMs) were revisited as a solution, showing promise in few-shot performance and cost-effectiveness.
- After iterative prompt tuning, Nova Lite matched or surpassed the performance of supervised models in most categories.
- The shift to LLMs represents a fundamental change in classifier development, reducing dependency on labeled data and annotation cycles.
- Supervised models remain viable for stable, large-scale datasets, but LLMs excel in dynamic or data-scarce environments.