Things Get Strange When AI Starts Training Itself

ChatGPT exploded into the world in the fall of 2022, sparking a race toward ever more advanced artificial intelligence: GPT-4, Anthropic's Claude, Google Gemini, and so many others. But with every passing month, tech corporations appear more and more stuck, competing over millimeters of progress. The most advanced and attention-grabbing AI models, having consumed most of the text and images available on the internet, are running out of training data, their most precious resource. This, along with the costly and slow process of using human evaluators to develop these systems, has stymied the technology's growth, leading to iterative updates rather than massive paradigm shifts. As researchers are left trying to wring water from stone, they are exploring a new avenue to advance their products: They're using machines to train machines.