Quantization is at the core of modern deep learning innovations, enabling faster, more efficient computations while reducing power and memory requirements. From its roots in compressing floating-point operations to its integration with cutting-edge frameworks like PyTorch, Just-In-Time (JIT) compilation, and TorchScript, quantization has become indispensable for AI scalability. This article explores the concept of quantization, … Continue reading Quantization in Deep Learning