Deep learning has advanced rapidly, driving breakthroughs in image recognition, natural language processing, and autonomous ...

Deepfakes are simple to make. A simple overview of the artificial intelligence (AI) behind deepfakes: Generative Adversarial Networks (GANs), Encoder-decoder pairs and First-Order Motion Models.

Almost two years after the acquisition by Intel, the deep learning chip architecture from startup Nervana Systems will finally be moving from its ...

A new computing architecture enables advanced machine-learning computations to be performed on a low-power, memory-constrained edge device. The technique may enable self-driving cars to make ...

Therefore, fitting deep learning models on MCUs can open the way for many applications. Memory bottlenecks in convolutional neural networks Architecture of convolutional neural network (CNN) ...

Deep learning has emerged as a cutting-edge tool for training computers to automatically perform activities like identifying stop signs, detecting a person’s emotional state, and spotting fraud.

These networks can already recognize images and play chess, for example. But in comparison to the human brain, deep learning can require up to 1,000 times more energy to perform the same functions.

The goal of the team’s study was to demonstrate the potential for deep-learning architecture to support early and reliable identification of cystic hygroma from first trimester ultrasound scans.