On Wednesday evening, Hurricane Milton will become the fifth hurricane in 2024 to make landfall in the mainland U.S. As storms like this one grow more frequent and intense, artificial intelligence is playing an increasingly central role in efforts by meteorologists and other scientists to track these storms and mitigate their harms. For years, meteorologists have built complex forecasting models of storms based on wind speeds, temperature, humidity and other factors, and recorded via readings from planes, buoys and satellites. But these models can take hours to produce updated forecasts. Machine learning models, on the other hand, draw upon vast knowledge of the earth's atmosphere and data from how previous storms have unfolded. They excel at pattern recognition, teasing out trends that most humans can't discern in a fraction of the time.

In recent years, engineers and computer scientists have created a wide range of technological tools that can enhance fitness training experiences, including smart watches, fitness trackers, sweat-resistant earphones or headphones, smart home gym equipment and smartphone applications. New state-of-the-art computational models, particularly deep learning algorithms, have the potential to improve these tools further, so that they can better meet the needs of individual users. Researchers at University of Brescia in Italy have recently developed a computer vision system for a smart mirror that could improve the effectiveness of fitness training both in home and gym environments. This system, introduced in a paper published by the International Society of Biomechanics in Sports, is based on a deep learning algorithm trained to recognize human gestures in video recordings. "Our commercial partner ABHorizon invented the concept of a product that can guide and teach you during your personal fitness training," Bernardo Lanza, one of the researchers who carried out the study, told TechXplore.

As museums worldwide strive to draw in young people, Tate Britain could place itself at the cutting edge with a project for Internet viewers to drive robots around its galleries at weekends, shining lights and cameras on artworks that loom out of the dark. The robot idea is one of four finalists for the new Tate IK Prize. The winning project will become a reality by the summer. "We wanted ways to use technology to increase our audience reach and new ways to connect people with art," said Jane Burton, the Tate's head of creative content. Another finalist proposes reproducing the gallery as a version of the popular Minecraft videogame.

It was a fall night in 2006, when Bradley Waldroup walked out of his rural trailer in southeastern Tennessee, carrying his .22 His estranged wife and her friend, Leslie Bradshaw, had just pulled up to drop off the Waldroups' four children. Waldroup began arguing with his wife and Bradshaw, who was unloading the car. He used a knife to cut her head open. He then chased his wife with the knife and a machete, managing to slice off one of her pinkies before dragging her into the trailer. There, he told their frightened children, "Come tell your mama goodbye," because it was the last time they'd ever see her. Miraculously, his wife managed to slip his grasp and escape.

Understanding what motivates serial killers to murder many times over can be difficult to grasp. Over the past few decades, scientists have begun building a clearer picture of the minds behind some of the most shocking crimes. According to the largest forensic neuroscience library in the world, there are surprising similarities between the abnormal brains structures of mass murderers. Pictured left is James Eagan Holmes, who was convicted on 24 counts of murder and 140 counts of attempted murder forr the 2012 Aurora shooting a movie theater. What's more, the differences are'at least 50 percent caused by genetics', raising the disturbing possibility that people can be born killers.