Sony’s PS Stars: a closer look at regional return plans

How we automated spot node selection with GKE compute classes to prevent expensive drift and cut our cloud costs by 50%.

As more code is AI-generated, it becomes critical to have controls, experimentation, and analytics built into product development workflows.

Benchmarks mislead AI teams. Discover a proven framework that the world's best teams use to build safer, higher-impact AI products.

The problem of multiple comparisons represents a fundamental clash between statistical inference and human intuition. In this blog post, we'll explain why our intuition leads us astray and review common methods to address it.

Randomization is one of the cornerstones of A/B testing. But why is randomization so important, and how can we achieve it? In this post, we'll address these two key questions.

In this post, we’ll show you how to speed up your A/B testing by using a wide toolbox of smarter statistical methods to shrink timelines from months to weeks.