artificial intelligence (AI) tagged posts

Japanese astronomers have developed a new artificial intelligence (AI) technique to remove noise in astronomical data due to random variations in galaxy shapes. After extensive training and testing on large mock data created by supercomputer simulations, they then applied this new tool to actual data from Japan’s Subaru Telescope and found that the mass distribution derived from using this method is consistent with the currently accepted models of the Universe. This is a powerful new tool for analyzing big data from current and planned astronomy surveys.

Wide area survey data can be used to study...

As more private data is stored and shared digitally, researchers are exploring new ways to protect data against attacks from bad actors. Current silicon technology exploits microscopic differences between computing components to create secure keys, but artificial intelligence (AI) techniques can be used to predict these keys and gain access to data. Now, Penn State researchers have designed a way to make the encrypted keys harder to crack.

Led by Saptarshi Das, assistant professor of engineering science and mechanics, the researchers used graphene — a layer of carbon one atom thick — to develop a no...

An international team of researchers led by Swinburne University of Technology has demonstrated the world’s fastest and most powerful optical neuromorphic processor for artificial intelligence (AI), which operates faster than 10 trillion operations per second (TeraOPs/s) and is capable of processing ultra-large scale data.

Published in the journal Nature, this breakthrough represents an enormous leap forward for neural networks and neuromorphic processing in general.

Artificial neural networks, a key form of AI, can ‘learn’ and perform complex operations with wide applications to computer vision, natural language processing, facial recognition, speech...

Novel training method could shrink carbon footprint for greener deep learning. Engineers have found a way to train deep neural networks for a fraction of the energy required today. Their Early Bird method finds key network connectivity patterns early in training, reducing the computations and carbon footprint for training deep learning.

Early Bird is an energy-efficient method for training deep neural networks (DNNs), the form of artificial intelligence (AI) behind self-driving cars, inte...