Artificial Intelligence

Neuralink is developing a fully-implanted, wireless, high-channel count brain-machine interface with the goal of enabling people with paralysis to directly use their neural activity to operate computers and mobile devices with speed and ease.

In artificial intelligence, deep learning organizes algorithms into layers (the artificial neural network) that can make its own intelligent decisions. To speed up the learning process, the new network was trained using the parameters of MobileNetV2, a mobile vision application, pre-trained on the ImageNet dataset with 1.4M images.

Researchers at Graphene Flagship partner, the Vienna University of Technology in Austria, hasve reported an image sensor with an integrated artificial neural network capable of learning and classifying images within nanoseconds. The chip is a thousand times faster and uses much less power than conventional vision technologies.

iCAD Inc announced that ProFound AI for 2D Mammography might notably reduce the risk of interval breast cancer, according to a retrospective analysis recently published in the Journal of Medical Screening.

Air pollution from the burning of fossil fuels impacts human health but predicting pollution levels at a given time and place remains challenging, according to a team of scientists who are turning to deep learning to improve air quality estimates.

The United States Army announced that it will work with Microsoft on the production phase of the Integrated Visual Augmentation System program as it moves from rapid prototyping to production and rapid fielding.

The all-new foiling Candela P-30—the world's fastest all-electric passenger ship—will hit Stockholm's waterways in 2022, shuttling passengers to and from the archipelago above the waves without wakes, noise and CO2 emissions.

Researchers have applied artificial intelligence methods to evaluate data of human embryo development. The AI based system photographs the embryos every five minutes, processes the data of their development and notifies any anomalies observed. This increases the likelihood of choosing the most viable and healthy early-stage embryo for IVF procedures.

Researchers have developed a machine learning algorithm that ranks drugs based on their efficacy in reducing cancer cell growth. The approach may have the potential to advance personalised therapies in the future by allowing oncologists to select the best drugs to treat individual cancer patients.