D-Wave Quantum Inc. expands beyond annealing into gate-model quantum with dual-rail speed/accuracy. Click to see why QBTS is ...

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 ...

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 ...

The simulation of strongly interacting many-body systems is a key objective of quantum physics research, as it can help to test the predictions of physics theories and yield new valuable insight.

Physicists have built a real-number version of quantum mechanics that makes all the same predictions as the standard theory, ...

Over the past few years, researchers have developed various quantum technologies, alternatives to classical devices that operate by leveraging the principles of quantum mechanics. These technologies ...

A team of scientists from Oak Ridge National Laboratory, Cleveland Clinic and IBM has calculated nine molecular ...