Architectures since GPT-2 still ride transformers. They crank memory and performance with RoPE, swap GQA for MLA, sprinkle in sparse MoE, and roll sliding-window attention. Teams shift RMSNorm. They tweak layer norms with QK-Norm, locking in training stability across modern models.
Trend to watch: In 2025, small, smart optimizations will matter more than big, complex system redesigns.
