The news archive provides access to past news stories from Communications of the ACM and other sources by date.
The University of Illinois' Naresh Shanbhag is pushing for a new computer architecture that blends computing and memory so devices can be smarter without consuming more energy.
ARSL is a new app that enables users to capture sign language with a smartphone camera and see a live translation into their native language.
Neuroscientists today know a lot about how individual neurons operate but remarkably little about how large numbers of them work together to produce thoughts, feelings and behavior.
The Trump administration's concern about China's growing technology clout is putting even more pressure on U.S. wireless carriers in their marketing battle over which company will be the first to offer 5G.
The HoneyBot is designed to deceive industrial hackers into exposing information to cybersecurity professionals.
Researchers have trained a machine learning system to search for debris disks around stars using telescopic data.
Students have designed and built a low-cost, three-dimensionally-printed robotic prosthetic hand that could provide a more affordable alternative for amputees.
ePave is a project to set up networks of self-powered wireless sensors under roads to provide updates on road conditions to transportation planners, drivers with connected cars, and others.
National University of Singapore researchers have developed a microfluidic chip that could identify minuscule amounts of biomolecules without intricate lab equipment.
JavaScript, Java, Python, PHP, and C# are the top five programming languages for the first quarter of 2018, according to the latest ranking by industry analyst firm Redmonk.
The French government will spend €1.5 billion ($1.85 billion) over five years to support research in artificial intelligence, encourage startups, and collect data that can be used, and shared, by engineers.
Companies are racing to develop hardware that more directly empowers deep learning.
Enabled by advances in computing power and neural networks, machines are getting better at recognizing and dealing with human emotions.
Computational theorists prove there is no easy algorithm to find Nash equilibria, so game theory will have to look in new directions.