A smaller, specialized AI model can generate better training data than a giant pre-trained one, unlocking real improvements in production systems.
Google used fine-tuned AI models to generate millions of relevance labels for app search results, solving a shortage of human-labeled training data. By combining these AI-generated labels with user behavior signals, they improved their App Store ranking system—especially for unpopular searches where user clicks are rare.