From the moment we put down the bows and the spears and made the first hoes and rakes and plows and wrote down the first ...

Researchers from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences have developed a neural network model based on self-attention mechanisms to rapidly predict radiation ...

Nextchip license NeuPro-M NPU to bring powerful and highly efficient AI capabilities to boost performance and capabilities of ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

Neural networks are one typical structure on which artificial intelligence can be based. The term neural describes their learning ability, which to some extent mimics the functioning of neurons in our ...

NTT Research announced at an event that it has started a new AI basic research group, dubbed the Physics of Artificial Intelligence Group.

In view of the abovementioned shortcomings, this article proposes a parallel dynamic multihop graph and composite multiscale convolution network for SU, referred to as PMGMCN. The network combines the ...

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

A Fortran-based feed-forward neural network library. Whilst this library currently has a focus on 3D convolutional neural networks (CNNs), it can handle most standard hidden layer forms of neural ...

The process involves a preprocessing step, a deep neural network (DNN) application step ... To guarantee real-time application, we also propose a graphics processing unit based parallel acceleration ...

Examples like Intel's Loihi chips tend to get competitive performance out of far lower clock speeds and energy use, but they ...