Why Data Quality is Becoming More Important Than Model Size in Modern AI Systems

For years, progress in artificial intelligence was closely tied to scaling laws, where increasing model size, dataset size, and compute power led to consistent performance improvements. Large-scale systems like GPT-4 and architectures such as Transformer architecture demonstrated that bigger models could achieve remarkable capabilities across language, vision, and multimodal tasks. However, recent developments suggest that simply increasing model size is no longer the most efficient or reliable