Ahmad Khan, president of KLA's Semiconductor Products and Customer Group, said in a CEO Summit keynote at SEMICON Taiwan 2026 that Moore's Law still matters but AI is changing how semiconductors innovate: transistor scaling alone can no longer carry performance gains, so innovation is widening from a single chip to system-level integration of logic, HBM and 3D DRAM, advanced packaging and high-speed interconnects. He noted that leading-edge GPU dies are so large that a wafer may yield only about five chips, so a single yield-critical defect costs far more, and once stacked DRAM becomes HBM integrated with the GPU on an interposer, "the final yield is the sum of all the parts." Beyond fatal defects, long, high-load AI training and inference runs make latent defects a growing concern; KLA's broadband plasma optical inspection systems generate roughly 125 TB of data per hour, nearly 3 PB a day, which must be sifted with GPU-based high-performance computing plus AI models and physics algorithms. Khan argued the next phase of competition depends on how fast the ecosystem turns faster innovation, richer information and deeper collaboration into "learning velocity."