The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.
Spiking neural networks (SNNs) closely replicate the structure of the human brain, making them an important step on the road to developing artificial intelligence. Researchers recently advanced a key technique for training SNNs using an evolutionary approach. This approach involves recognizing and making use of the different strengths of individual elements of the SNN.
Berkeley Lab researchers participated in a study that used machine learning to scan for new particles in three years of particle-collision data from CERN’s ATLAS detector.
SUMMARYResearchers at the George Washington University, together with researchers at the University of California, Los Angeles, and the deep-tech venture startup Optelligence LLC, have developed an optical convolutional neural network accelerator capable of processing large amounts of information, on the…
Data from a new study presented this week at The Liver Meeting Digital Experience® – held by the American Association for the Study of Liver Diseases – found that using neural networks, a type of machine learning algorithm, is a more accurate model for predicting waitlist mortality in liver transplantation, outperforming the older model for end-stage liver disease (MELD) scoring. This advancement could lead to the development of more equitable organ allocation systems and even reduce liver transplant waitlist death rates for patients.
The field of “brain-mimicking” neuromorphic electronics shows great potential for basic research and commercial applications, and researchers in Germany and Switzerland recently explored the possibility of reproducing the physics of real neural circuits by using the physics of silicon. In Applied Physics Letters, they present their work to understand neural processing systems, as well as a recipe to reproduce these computing principles in mixed signal analog/digital electronics and novel materials.
Recent advances in unmanned‐aerial‐vehicle‐ (UAV‐) based remote sensing utilizing lightweight multispectral and thermal infrared sensors allow for rapid wide‐area landmine contamination detection and mapping surveys. We present results of a study focused on developing and testing an automated technique of…
To better leverage cancer data for research, scientists at ORNL are developing an artificial intelligence (AI)-based natural language processing tool to improve information extraction from textual pathology reports. In a first for cancer pathology reports, the team developed a multitask convolutional neural network (CNN)—a deep learning model that learns to perform tasks, such as identifying key words in a body of text, by processing language as a two-dimensional numerical dataset.
Scientists have developed space junk identification systems, but it has proven tricky to pinpoint the swift, small specks of space litter. A unique set of algorithms for laser ranging telescopes, described in the Journal of Laser Applications, by AIP Publishing, has significantly improving the success rate of space debris detection.
What did Vincent van Gogh actually paint and draw? Paintings and drawings fade, so researchers from TU Delft are using deep learning to digitally reconstruct works of art and discover what they really looked like. ‘What we see today is not the painting or drawing as it originally was,’ says researcher Jan van der Lubbe.