Algorithm designs optimized machine-learning models up to 200 times faster than traditional methods.
Taking a cue from biological cells, researchers from MIT, Columbia University, and elsewhere have developed computationally simple robots that connect in large groups to move around, transport objects, and complete other tasks.
A new computer program that spots when information in a quantum computer is escaping to unwanted states will give users of this promising technology the ability to check its reliability without any technical knowledge for the first time.
Working together, researchers at the University of Sydney and UNSW have overcome a fundamental hurdle to building quantum computers in silicon.
Researchers at Linköping University have developed a theoretical model that enables simulations for showing what happens in hard cutting materials as they degrade. The model will enable manufacturing industry to save both time and money.
Deciding when an athlete can return to the game after a head injury makes managing the treatment of sports-related concussions very complicated. A team of scientists are teaching machines how to predict recovery time from sports-related concussions based on symptoms like headache, dizziness and fatigue. Results from their study can be used as the foundation for a decision support system that would help clinicians to develop individualized treatment for injured athletes.
For the first time researchers have demonstrated a new way to perform functions essential to future computation three orders of magnitude faster than current commercial devices. The team lead by Associate Professor Shinobu Ohya, created a nanoscale spintronic semiconductor device that can partially switch between specific magnetic states trillions of times a second (terahertz -- THz), far beyond frequencies of devices at present.
A new study debunks a popular, two-decade-old theory about the shape of networks.
Scientists at the University of Sydney have for the first time demonstrated improvement in quantum computers by using codes designed to detect and discard errors in the logic gates of such machines. The codes were applied to IBM's quantum computer via IBM Q.
The aptly named software package Whetstone enables neural computer networks to process information up to 100 times more efficiently than current standards, making possible an increased use of artificial intelligence in mobile phones, self-driving cars, and image interpretation.