The latest AI models continue to grow in size and complexity, demanding increasing amounts of compute performance for training and inference—far beyond what Moore’s Law can keep up with. That’s why NVIDIA engages in extreme codesign . Designing across multiple chips and a mountain of software cohesively enables large generational leaps in AI factory performance and efficiency. Lower-precision AI formats are key to improving compute performance and energy efficiency. Bringing the benefits of ultra-low-precision numerics to AI training and inference while maintaining high accuracy requires extensive engineering across every layer of the technology stack. It spans the creation of the formats, implementation in silicon, enablement across many libraries, and working closely with the ecosystem to deploy new training recipes and inference optimization techniques.…