Data Acquisition Strategy for a New AI Application
Given the scenario below, evaluate the two primary strategies for acquiring instruction data (manual human creation vs. automatic computational generation). Recommend which strategy the company should prioritize and justify your decision by explaining the trade-offs of each approach in this specific context.
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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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Manual Data Generation for Instruction Fine-Tuning
Crowdsourcing Data for Fine-Tuning
Automatic Data Generation for Instruction Fine-Tuning
Data Acquisition Strategy for a New AI Application
A research lab is developing a new instruction-following model and is considering different ways to create its training data. Match each characteristic or goal below with the most appropriate data generation strategy.
A company aims to create a fine-tuning dataset for a chatbot that specializes in medical advice. They use their most advanced, general-purpose language model to generate 100,000 question-and-answer pairs based on medical textbooks. Then, a team of doctors reviews every pair, correcting any errors and rewriting answers to ensure they are safe and accurate. Which statement best analyzes this data acquisition approach?