Strategy for a Real-Time Q&A System
A development team is building a real-time question-answering system for customer support. The system must provide answers quickly and stay within a fixed monthly cloud computing budget. The team has tested three search configurations with the following results. Based on this data, which configuration should the team choose? Justify your decision by evaluating the trade-offs presented.
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Ch.5 Inference - 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
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Strategy for a Real-Time Q&A System
A team is tuning a text generation model and has collected the following data on the trade-off between computational cost (in processing units) and output quality (on a 100-point scale) for different search configurations.
- Configuration A: Cost = 10 units, Quality = 80
- Configuration B: Cost = 20 units, Quality = 90
- Configuration C: Cost = 40 units, Quality = 94
- Configuration D: Cost = 80 units, Quality = 95
Based on this data, which configuration represents the most effective balance between improving output quality and maintaining computational feasibility?
Critique of a 'Maximum Search' Strategy