trade-off
term_id: trade_off
Category: basic_concepts
Definition
In AI and engineering, a trade-off refers to the balance required when optimizing conflicting objectives, such as model accuracy versus computational cost or latency versus precision. Since resources like memory, time, and energy are finite, improving one metric often degrades another. Understanding these trade-offs is critical for selecting the right model architecture and deployment strategy for specific hardware constraints and application requirements.
Summary
A compromise where gaining advantage in one area results in a loss in another.
Key Concepts
- Resource allocation
- Optimization
- Accuracy vs. Speed
- Bias-Variance
Use Cases
- Selecting model size for edge devices
- Balancing inference latency with prediction accuracy
- Managing memory usage during training