You don't have to wear a Halloween mask to avoid being detected by facial recognition software: a dab of makeup will do the trick, according to a new study. Researchers at Ben-Gurion University in Beersheba, Israel, developed an artificial intelligence that shows users where to apply some foundation or rouge to fool face-recognition algorithms into thinking they're looking at a different person. The researchers tested their scheme against ArcFace, a machine-learning model that takes two facial images and determines the likelihood they're the same person. The team used 20 volunteers (10 men and 10 women) in a real-world environment using two cameras and a variety of lighting conditions and shooting angles. Participants wearing'adversarial makeup,' as recommended by the program, tricked the system 98.8 percent of the time.

Scientists have created an algorithm that analyzes RF signals in order to monitor you in your sleep. It uses a device similar to a Wi-Fi router to determine everything from how shallow your breathing is to whether you're having a dream or not. The study was conducted by a group consisting of researchers from MIT and Massachusetts General Hospital's Division of Sleep Medicine. Imagine if your Wi-Fi router knows when you are dreaming, and can monitor whether you are having enough deep sleep, which is necessary for memory consolidation. Our vision is developing health sensors that will disappear into the background and capture physiological signals and important health metrics, without asking the user to change her behavior in any way. The sensor works by sending out low-level RF signals that bounce off of people.

The idea of a robot that can learn and function on its own, without the need for any human help, might sound like the plot to the latest science fiction blockbuster. But scientists have got one step closer to making this a reality with the creation of the first artificial brain connection that can learn autonomously. The groundbreaking study represents a big step toward intelligent machines that learn without the need for human input. Researchers have long-looked to the human brain for inspiration in creating an intelligent machine that can learn. The tiny electronic component consists of a thin layer of material sandwiched between two electrodes.