For years, the formula for better performance was simple: more data and more compute. But we are reaching a point where there is no more human-generated text left on the open web to ingest. This data wall is forcing researchers to find creative ways to keep the learning process alive.
The Limits of Human Text
Most of what is published online is either repetitive or low quality, making it unsuitable for training advanced systems. High-quality data, such as specialized medical journals or proprietary codebases, is now the most sought-after commodity. The era of free, unlimited training material is effectively over.
The Rise of Synthetic Data
To solve the shortage, some are using models to generate data for other models to learn from. However, this carries the risk of model collapse, where errors are compounded over generations. Finding the balance between synthetic and organic information is the next great technical hurdle.