Meta GEM training efficiency shows why LLM-scale recommenders need workload-specific kernels, precision, parallelism, memory, and profiling.
Training a frontier AI model in 2026 requires tens of thousands of GPUs working in tight synchronization for months. Yet the factor that most often li