Sophisticated AI models tend to require a lot of memory and take up a lot of storage space. One of the ways to reduce that ...

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...

Model quantization bridges the gap between the computational limitations of edge devices and the demands for highly accurate models and real-time intelligent applications. The convergence of ...

One of the most widely used techniques to make AI models more efficient, quantization, has limits — and the industry could be fast approaching them. In the context of AI, quantization refers to ...

You can now download Gemma 4 models with quantization-aware training to reduce the amount of mobile memory required to 1GB.

Researchers at Nvidia have developed a novel approach to train large language models (LLMs) in 4-bit quantized format while maintaining their stability and accuracy at the level of high-precision ...

Microsoft Corp. said today it’s advancing the local artificial intelligence development capabilities of Windows, as part of an effort to help developers build and experiment and reach new users with ...