Challenges in Traditional Data Acquisition
Several factors are driving the search for alternatives to human-generated training data:
1. Human Limitations
- Speed: There's a cap on how quickly humans can produce high-quality annotations.
- Bias: Human annotators may introduce their own biases into the data.
- Errors: Misinterpretation of labeling instructions or simple mistakes can compromise data quality.
- Cost: Paying for human annotation at scale is expensive.