In mathematics and digital signal processing, quantization is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite …

Nov 6, 2025 · Quantization is a model optimization technique that reduces the precision of numerical values such as weights and activations in models to make them faster and more efficient.

Quantization is the process of mapping continuous infinite values to a smaller set of discrete finite values. In the context of simulation and embedded computing, it is about approximating real-world …

Quantization is the process of reducing the precision of a digital signal, typically from a higher-precision format to a lower-precision format. This technique is widely used in various fields, including signal …

Nov 24, 2025 · Quantization has emerged as a crucial technique to address this challenge, enabling resource-intensive models to run on constrained hardware. The NVIDIA TensorRT and Model …

Jul 20, 2025 · Among many optimization techniques to improve AI inference performance, quantization has become an essential method when deploying modern AI models into real-world services.

What is quantization in machine learning? Quantization is a technique for lightening the load of executing machine learning and artificial intelligence (AI) models. It aims to reduce the memory …

Feb 10, 2026 · What is quantization in the world of large language models, and how much does it actually impact precision?

Learn about quantization in digital communication, including its importance, types, and effects on signal processing.

Jun 11, 2025 · Learn the fundamentals of quantization in signal processing, its applications, and the different techniques used to achieve optimal results.