AI Reliability: What It Is, Why It Matters, and How to Fix It

The article highlights the critical issue of AI reliability, where systems fail in production despite good benchmark scores because they are evaluated on static data, not real-world inputs. It argues that the problem lies in measuring the wrong aspects of AI performance, leading to unexpected failures post-deployment.