Team Green has succeeded in leaving me excited for the future of upscaling in games with DLSS 4, and I hope AMD can do the ...

The Microsoft piece also goes over various flavors of distillation, including response-based distillation, feature-based ...

Twelve University of Wyoming projects have been selected for seed funding for the application of artificial intelligence (AI) technologies to various areas of investigation.

Researchers from Australia and Bangladesh have developed an artificial intelligence model capable of spotting and ...

This year at CES, Nvidia presented the next generation of its DLSS upscaling technology, which is trained with the help of artificial intelligence, alongside the new GeForce RTX 5090, 5080, and 5070 ...

The core innovation of this technology lies in the design and implementation of the Quantum Convolutional Neural Network (QCNN). The QCNN not only fully replicates the output of classical CNNs but ...

In this study, we propose a novel algorithmic trading model CNN-TA using a 2-D convolutional neural network based on image processing properties. In order to convert financial time series into 2-D ...

In this paper, we introduce TMCNet, a novel end-to-end deep learning model that integrates multi-scale 3D convolutional neural networks with Transformer for enhanced feature extraction. First, the ...

Learn More A new neural-network architecture developed by researchers at Google might solve one of the great challenges for large language models (LLMs): extending their memory at inference time ...

Red Hat, the IBM-owned open-source software giant, has completed its acquisition of Neural Magic, a pioneering artificial intelligence (AI) optimization startup. Initially announced in November ...

It’s genuinely clever, and it uses AI in real time to work it all out – there are basically loads of neural networks processing the game data live as you play, learning what’s in the scene ...

The underlying principle is the spiking neural network (SNN) — where a neural network is a collection of machine learning algorithms and the spikes it produces are akin to the signals produced ...