Floating Point Precision, Low Precision, Aı, Machine Learning Ai, Llm.
optimized for floating-point computations and are widely used for accelerating AI and ML workloads. Memory Optimisation Model Compression: Lowering precision (e.g., from FP32 to FP16) reduces memory requirements, enabling larger models to fit into memory or reducing memory bandwidth constraints.