A/B Testing

Sat, 18 Jul 2026 09:43:55 +0000

Definition

A/B testing is a randomized controlled experiment where two variants, A and B, are compared to evaluate which yields better results in a specific metric. In AI engineering, it is crucial for optimizing model performance, user interface designs, or recommendation algorithms. By isolating variables and measuring outcomes against a control group, teams can make data-driven decisions to improve system efficacy and user engagement without relying on intuition.

Summary

A statistical method comparing two versions of a variable to determine which performs better.

Experimentation on English AI Terms Dictionary

A/B Testing

Definition

Summary