The three-dimensional world of ordinary experience—the universe filled with galaxies, stars, planets, houses, boulders, and ...

There has been much written about the potential for FPGAs to take a leadership role in accelerating deep learning but in practice ... being used to connect pool/LRN kernels for CNNs. As the diagram ...

Depending on the deep learning architecture, data size, and task at hand, we sometimes require 1 GPU, and sometimes, several of them, a decision data scientist needs to make based on known ...

Neural architecture search is an aspect of AutoML, along with feature engineering, transfer learning, and hyperparameter optimization. It’s probably the hardest machine learning problem ...

To address this issue, researchers at ETH Zurich have unveiled a revised version of the transformer, the deep learning architecture underlying language models. The new design reduces the size of ...

today announced the development of a high-speed and high-energy-efficiency algorithm and hardware architecture for deep learning processing with less degradations of recognition accuracy.