In the future, quantum computers may be able to solve problems that are far too complex for today’s most powerful supercomputers. To realize this promise, quantum versions of error correction codes must be able to account for computational errors faster than they occur.
Researchers from the RIKEN Center for Quantum Computing have used machine learning to perform error correction for quantum computers—a crucial step for making these devices practical—using an autonomous correction system that despite being approximate, can efficiently determine how best to make the necessary corrections.
Memories can be as tricky to hold onto for machines as they can be for humans.
The past may be a fixed and immutable point, but with the help of machine learning, the future can at times be more easily divined.
Green Bronx Machine, an impact driven, non-profit organization is partnering with DNB Bank ASA to provide 105 laptops to underprivileged students living in the poorest congressional district in the United States.
• A university-industry collaboration has successfully run a quantum algorithm on a type of quantum computer known as a cold atom quantum computer for the first time. The achievement by the team of scientists from the University of Wisconsin¬–Madison, ColdQuanta and Riverlane brings quantum computing one step closer to being used in real-world applications.
The Coalition for Academic Scientific Computation, or CASC — a network of more than 90 research computing-focused organizations from academic institutions, national labs, and research centers around the U.S. — hopes to continue to bring this critical computing work to the forefront through its activities. Newly elected leadership and recent changes within CASC are helping the nonprofit organization excel in this mission.
Using a computerized and completely remote training program, researchers have found a way to mitigate negative emotions in children. Results support the link between inhibitory control dysfunction and anxiety/depression. EEG results also provide evidence of frontal alpha asymmetry shifting to the left after completing an emotional version of the training. Computerized cognitive training programs can be highly beneficial for children, not just for academics, but for psychological and emotional functioning during a challenging time in their development.
A team of quantum theorists seeking to cure a basic problem with quantum annealing computers—they have to run at a relatively slow pace to operate properly—found something intriguing instead.
Applying his passions for science and art, Nikhil Tiwale—a postdoc at Brookhaven Lab’s Center for Functional Nanomaterials—is fabricating new microelectronics components.
Four Rutgers professors have been named fellows of the American Association for the Advancement of Science (AAAS), an honor given to AAAS members by their peers. They join 485 other new AAAS fellows as a result of their scientifically or socially distinguished efforts to advance science or its applications. A virtual induction ceremony is scheduled for Feb. 13, 2021.
For more than 25 years, Binghamton University’s Jessica Fridrich has studied digital-image steganography — the science of hiding messages inside ordinary-looking photos. Just as technology has evolved and become more sophisticated, so have the methods to share secrets — and a recent $768,964 grant from the National Science Foundation will help Fridrich stay ahead of the curve.
Researchers from Binghamton University have teamed up with Intel to develop a tool called FakeCatcher, which can detect deepfake videos at an accuracy rate above 90%.
New Brunswick, N.J. (June 1, 2020) – Rutgers University–New Brunswick Professor Ahmed Elgammal is available for interviews on the future of art and creativity in the age of artificial intelligence (A.I.). “As artificial intelligence becomes an increasing part of our…
Researchers reporting in ACS Nano have developed a new manufacturing process that could enable ultra-efficient atomic computers that store more data and consume 100 times less power.
A study conducted by the University at Albany, the National Institutes of Health and New York University Langone Medical Center uncovered several new findings about the amount of time children spend watching television or using a computer or mobile device.
Researchers at Michigan State University say that true, human-level intelligence remains a long way off, but their new paper published in The American Naturalist explores how computers could begin to evolve learning in the same way as natural organisms did – with implications for many fields, including artificial intelligence.