Lifeboat Foundation

Researchers at the University of Washington have used machine learning to teach an AI system to identify when someone is having a cardiac arrest. The system learned to identify agonal breathing, which occurs when someone gasps for breath during cardiac arrest, with a high degree of accuracy. The technology can be embedded into a variety of listening devices, such as smart speakers or smartphones, to alert authorities and loved ones to someone having a heart attack while they sleep.

Approximately half a million Americans die from cardiac arrest annually. Cardiac arrests often happen while someone is at home in bed. This is particularly dangerous, as there is likely to be no-one around, or no-one awake, to help.

Now, researchers have developed an AI system that can work through smart speakers or a smartphone to monitor for signs of a cardiac arrest while someone sleeps. The system listens for something called agonal breathing, which occurs in about 50% of people who experience a cardiac arrest, and patients who demonstrate this characteristic gasping often have a better chance of surviving.

“Machine Learning: Living in the Age of AI,” examines the extraordinary ways in which people are interacting with AI today. Hobbyists and teenagers are now developing tech powered by machine learning and WIRED shows the impacts of AI on schoolchildren and farmers and senior citizens, as well as looking at the implications that rapidly accelerating technology can have. The film was directed by filmmaker Chris Cannucciari, produced by WIRED, and supported by McCann Worldgroup.

A team of researchers from Carnegie Mellon has made a breakthrough in the field of noninvasive robotic device control. Using a noninvasive brain-computer interface, they have developed the first-ever successful mind-controlled robotic arm exhibiting the ability to continuously track and follow a computer cursor.

Advancement of artificial intelligence (AI) prompts fears of a Terminator-style future where humans live as an underclass to the machines we created. However, humanity may face a far more immediate threat in the form of AI malware.

Researchers from CSIRO’s Data61, the data and digital specialist arm of Australia’s national science agency, have developed a world-first set of techniques to effectively ‘vaccinate’ algorithms against adversarial attacks, a significant advancement in machine learning research.

The system tracks and alarms when items move past the register without being scanned.

Anyone who tells you the robot apocalypse is upon us—that the machines will not stop stealing our jobs, that they are gearing up to chase us through the streets while doing backflips and fighting off stick-wielding humans—has never tried to program a robot. It’s difficult to get a machine to do so much as move an arm, which requires the precise control and coordination of joint angles and torque.

The difficulty of programming robots is a problem that Facebook, of all companies, wants to fix. Today the social network continues its unlikely dive into robotics by open-sourcing a new robot framework, known as PyRobot, that could simplify the way researchers program their machines, and could even make it easier for non-robotics types to jump into the field. If programming robots has so far been something like wading through a command-line interface, PyRobot promises to be like gliding through the sleekness of macOS. At least, that’s the hope: Many others have tried and failed to do this kind of thing.

Understanding electrons’ intricate behavior has led to discoveries that transformed society, such as the revolution in computing made possible by the invention of the transistor.

Dishwashers already make our washing automated. This robot uses AI scanners for extra cleanliness.