Floating Point Precision, Low Precision, Aı, Machine Learning Ai, Llm.
Layers: Fully connected layers, convolutional layers, and recurrent layers rely on floating point computations for forward and backward passes. Quantization Inference: After training, models can be quantized to lower precision formats like FP16 or INT8 to improve efficiency and reduce memory usage