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Data Generation Strategy for a Specialized AI Assistant
A startup is building an AI assistant to provide technical support for a complex software product. They have a limited budget for creating the data needed to train their model. They are considering two options:
- Hiring a small team of expert software engineers to manually write 5,000 high-quality question-and-answer pairs.
- Using a powerful, general-purpose language model to automatically generate 100,000 question-and-answer pairs based on the software's documentation.
Evaluate the two options. Which strategy would you recommend for the startup? Justify your recommendation by analyzing the key trade-offs between the two approaches regarding data scale, cost, and potential quality.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Evaluation in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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