Sports analytics has always been about finding signals in noise. There are a thousand variables competing for attention, and ninety-nine percent of them are irrelevant. The art of traditional sports analysis has been figuring out which variables matter and then building models around them. However, human cognition has its limits. We can only hold so many variables in our heads simultaneously. Artificial intelligence doesn't have that constraint. Transformer-based machine lear

The Delhi High Court is hearing a case that will determine whether artificial intelligence companies can use copyrighted work to train their models without permission. Asian News International, a major Indian news agency, sued OpenAI in late 2024 for using its copyrighted news articles to train ChatGPT without authorization or compensation. The case has moved through 2025 and continues into 2026, and its implications extend far beyond India. The case makes us think whether us

When Meta announced it was buying a 49% stake in Scale AI for $14.3 billion this January, it wasn't really about data labeling anymore, but more about integration. Scale AI didn't change its product that day. But its incentive structure changed completely. Now, every feature they build, every market they target, every partnership they sign gets filtered through one question: does this work for Meta? This is happening across the AI startup ecosystem. It's reshaping which compa