As artificial intelligence grows more powerful, so does its appetite for speed and energy. The quest for faster, smarter ...
Researchers from Peking University say their resistive random-access memory chip may be capable of speeds 1,000 faster than ...
Quantum Computing Pioneer Integrates QPU with Augmented Data Support for Machine Learning And AI into NVIDIA CUDA-Q Platform ...
The Seeker quantum processor from Quantum Circuits now supports Nvidia's CUDA-Q, enabling developers to combine quantum ...
On November 15, 2019, the Federal Circuit issued an opinion in Koninklijke KPN N.V. v. Gemalto M2M GmbH et al., 2018-1863, that provides additional guidance on the patentability of data ...
Researchers at the Georgia Tech Research Institute recently combined machine learning, field-programmable gate arrays (FPGAs), graphics processing units (GPUs), and a novel radio frequency image ...
Quantum Circuits, Inc., announced an integration with NVIDIA’s hybrid quantum-classical platform, NVIDIA CUDA-Q, - Read more ...
Researchers at the Cockrell School of Engineering at The University of Texas at Austin have found a way to make the new generation of smart computers more energy efficient. Traditionally, silicon ...
New research finds that magnetic wires, spaced a certain way, can lead to a 20-30x reduction in the amount of energy needed to run neural network training algorithms. The rapid progression of ...