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 ...

Compacting an AI model to run faster. AI quantization is primarily performed at the inference side (user side) so that it can run more quickly in phones and desktop computers. For example, whereas the ...

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 ...

It turns out the rapid growth of AI has a massive downside: namely, spiraling power consumption, strained infrastructure and runaway environmental damage. It’s clear the status quo won’t cut it ...

Google Quantum AI and Keysight joined forces to enhance Quantum circuit simulations with frequency-domain flux quantization Provides an extended library of quantum devices and a robust circuit design ...