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 ...

A smaller, cheaper AI usually means a dumber one. A new technique flipped that—and your phone might be the winner.

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 ...

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 ...

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...

Rapid advances in applying artificial intelligence to simulations in physics and chemistry have some people questioning whether we will even need quantum computers at all. Tech companies have been ...