How to Improve Data Labeling Efficiency
with Auto-Labeling, Uncertainty Estimates,
and Active Learning
Auto-Label AI, although extremely powerful, cannot always be 100% accurate. Which is exactly why you need to measure and evaluate how much you can trust the model output when utilizing auto labeling for data annotation.
In this whitepaper, we dive into the machine learning theory and techniques that were developed to evaluate our auto-labeling AI. More specifically, how the platform estimates the uncertainty of auto-labeled annotations and applies it to active learning.