As analytics becomes core to decision-making, companies are pushing the boundaries of their IT systems to take advantage of data-driven technologies.
Artificial intelligence is helping health-care professionals do their jobs better, giving them the tools to build a smarter, more efficient ecosystem.
AI technologies promise to extend human capabilities, writes SAS chief executive Jim Goodnight, and ultimately, improve the world around us.
Going far beyond traditional attack detection, sophisticated machine learning systems help organizations stay one step ahead of fraudsters.
IT security tools are becoming increasingly sophisticated thanks to artificial intelligence, but advances in the cybercriminal world are close behind.
Market forces mean the region’s consumers could benefit earliest from open banking innovation, writes Mastercard’s Rama Sridhar.
The computers that run our auto, lighting, and other systems can’t handle modern encryption standards. Now the US government is working on a fix.
The systems are becoming the go-to foundation for ensuring innovation, agility, and an exceptional customer experience.
The discipline, which draws on psychology, is seeing a renaissance, writes Michelle Baddeley. But it wasn’t always distinct from its “rational” cousin.
To address a critical gap in health-care resources, the region is becoming a center of innovation in health-care artificial intelligence, robotics, and automation.
NOTES: Health-care roles automated by AI, 5 yrs
To prove business value, analytics initiatives need to move past the data-gathering pilot phase, says SAS’s Oliver Schabenberger.
The practice focuses on collaboration and automation to speed delivery of analytics—and accelerate innovation.
Technological advances will continue to expand our understanding of the cosmos, writes Martin Rees. They may also offer a glimpse into the future of the human species.
Today’s fast-changing workplaces need employees who can keep up with advances in technology—and employers who can remove the obstacles to retraining.
Building robust and comprehensive responses to the ethical challenges, real and hypothetical, raised by AI is far from straightforward.