AI stands at a quiet yet decisive turning point. The past few years of generative AI breakthroughs were powered by what might be called the “scaling myth”:“The bigger the model, the smarter the AI.”But that assumption is now showing cracks.Performance gains from simply enlarging models are slowingHigh-quality training data is running scarceTraining costs are rising exponentiallyTransformer-based architectures are approaching saturationThe era when sheer scale could reliably drive progress is ...