How machines learned precision
A new study shows that machine learning models can achieve human‑level precision in tasks like image recognition and natural language processing by training on increasingly large and diverse datasets. Researchers found that as models grow in size and complexity, their error rates drop sharply, suggesting that scaling up is key to achieving reliable, precise performance across domains.