Training: How AI Gets Smarter

Right now, there are AIs that became superhuman at Go in just a few days—starting from zero, no human strategies, no old games to copy. In this episode, we’ll step inside that training loop and ask: how does “random guesses” turn into “smarter than experts”?

In 2011, top-tier vision systems still misclassified images about one in four times on ImageNet. Six years and 14 million labeled photos later, that error had plunged to 3%—better than most humans. That jump wasn’t “magic”; it was the result of brutal, methodical training.

In this episode, we zoom out from a single training loop and look at what really makes AI improve: not just more cycles, but smarter cycles. The choice of data, the way feedback is given, and even how “mistakes” are measured can change a model from barely useful to world-class.