Scaling Laws Without Power Laws: Why Bigger Models Still Win
Budget meetings have a way of making AI theory suddenly less philosophical. Someone asks the simple question: “If we double the model size or the training data, how much better does the system get?” Then someone else opens a spreadsheet, adds a few curves, and everyone pretends the future has become manageable. This ritual has powered a large part of modern AI investment. Scaling laws made model development feel less like guesswork and more like engineering. ...