Many animals, and an increasing number of artificial agents, display sophisticated capabilities to perceive and manipulate objects. But human beings remain distinctive in their capacity for flexible, creative tool use -- using objects in new ways to act on the world, achieve a goal, or solve a problem. Here we introduce the "Tools" game, a simple but challenging domain for studying this behavior in human and artificial agents. Players place objects in a dynamic scene to accomplish a goal that can only be achieved if those objects interact with other scene elements in appropriate ways: for instance, launching, blocking, supporting or tipping them. Only a few attempts are permitted, requiring rapid trial-and-error learning if a solution is not found at first. We propose a "Sample, Simulate, Update" (SSUP) framework for modeling how people solve these challenges, based on exploiting rich world knowledge to sample actions that would lead to successful outcomes, simulate candidate actions before trying them out, and update beliefs about which tools and actions are best in a rapid learning loop. SSUP captures human performance well across 20 levels of the Tools game, and fits significantly better than alternate accounts based on deep reinforcement learning or learning the simulator parameters online. We discuss how the Tools challenge might guide the development of better physical reasoning agents in AI, as well as better accounts of human physical reasoning and tool use.

Tiny self-propelled capsules shed their outer shells and deliver drugs directly to tumour cells. These microrobots, demonstrated in mice intestines, could one day be targeted treatments for cancers in hard to reach places in the body. "When the capsule reaches the tumour, we can activate it, break the capsule, release the micromotors and they will move around the tumour area. That motion is very important for drug delivery," says Wei Gao at the California Institute of Technology in Pasadena. He and his team created the micromotors in a series of layers.

Almost 70,000 gamers are set to crowd Los Angeles Convention Center for the annual E3 expo, a highlight on the video game calendar. Some of the top attractions are esports, with competitions throughout the week attracting fans in droves. Fernando Lewis knew he was good at video games like Madden NFL and NBA 2K, but he wanted a better barometer of his skills. He signed up for some tournaments, but it wasn't easy to get regular competition in between them. Then he found Play One Up.

Machine learning is an increasingly prevalent buzzword in the media. Its applications in science and the private sector are frequently discussed--but what about global development? Can it also help advance fields like health, agriculture, and financial inclusion? That's because it can help us uncover previously invisible patterns in data, to identify the most effective solutions and target them in the right way. Machine learning (ML) has been around for decades, but now is our chance to apply it to development challenges in new ways, for three reasons.

Chethan Pandarinath wants to enable people with paralysed limbs to reach out and grasp with a robotic arm as naturally as they would their own. To help him meet this goal, he has collected recordings of brain activity in people with paralysis. His hope, which is shared by many other researchers, is that he will be able to identify the patterns of electrical activity in neurons that correspond to a person's attempts to move their arm in a particular way, so that the instruction can then be fed to a prosthesis. Essentially, he wants to read their minds. "It turns out, that's a really challenging problem," says Pandarinath, a biomedical engineer at the Georgia Institute of Technology in Atlanta. "These signals from the brain -- they're really complicated."

This afternoon, SpaceX is slated to launch its latest cargo mission from Florida for NASA, sending about 5,000 pounds of supplies to the crew on the International Space Station. For this mission, the company is employing a Dragon cargo capsule that's already been to space twice before. If successful, it'll be the first time the same Dragon has gone on a third trip to space. Packed inside the Dragon's main storage compartment are some interesting goodies and science experiments for the crew to work with over the next few months. These include a printer designed to create 3D organ-like tissues in space, as well as an experiment to culture cells taken from patients with multiple sclerosis and Parkinson's disease. The launch will also be carrying a key piece of hardware for the station itself.

TOKYO (Reuters) - Miniature remote controlled cars have proved to be a crowd pleaser at track and field throwing events, but for the Tokyo 2020 Olympics Toyota Motor Corp is upping the game with a hi-tech way to fetch javelins and hammers: pint-sized, self-driving A.I. robot cars. The Japanese automaker on Monday unveiled a prototype of its next-generation field support robot, a miniature shuttle bus-shaped contraption based on its "e-Palette" ride-sharing vehicle under development, to be used at the Tokyo Games. The vehicle, roughly the size of a toddler's ride-on toy car, can travel at a maximum speed of 20 kilometers per hour and sports three cameras and one lidar sensor which enable it to "see" its surroundings. Draped around the top of its body is a band of LED lights which illuminate when the vehicle uses artificial intelligence to follow event officials toward the equipment hurled by athletes onto the pitch during shot put, discus throw, hammer throw and javelin events. After the equipment, which can weigh as much as eight kilograms for hammers, is loaded into the vehicle by the official, a press of a button located toward its front sends the car zipping back to athletes for later use.

You have your sleeping bag at the office for those overnight non-stop coding deadlines that require you to work on the AI system until you get the particular component working right. Turns out, you've been using the sleeping bag quite a bit lately. Furthermore, you often find yourself telling friends that you cannot spare time to go with them to an evening excursion at the local pubs, due to having to stay at work. The moment you get to work in the morning, you are bombarded with tons of very intense coding to be done, and of course eating lunch at your desk is the only means to try and keep your head above water (no time to go out and get food or heaven forbid sit at a restaurant and eat lunch there). It's a do-or-die culture at the workplace and you are immersed in it up to your teeth. Welcome to the typical workplace conditions for AI developers doing AI self-driving driverless autonomous car systems work. In fact, if you were to go from building to building in a place like Silicon Valley, you are likely to find tons of developers all suffering the same fate.

Today people all around the world will be celebrating the 50th anniversary of one of humanity's greatest technological achievements: landing on the Moon. Technology has undergone immense change since 1969. The computer systems and software that took Neil Armstrong, Buzz Aldrin, and Michael Collins to our nearest celestial neighbor pale in comparison to the smartphones we carry around in our pockets today. Fifty years on, as we set our sights on a return to the Moon, as well as future human spaceflight to Mars and beyond, what are the innovations that will get us there? Research institutions and national labs across the globe are pouring hundreds of thousands of research hours into every conceivable aspect of space science.

This fall, the School of Science will welcome four new members joining the faculty in the departments of Biology, Brain and Cognitive Sciences, and Chemistry. Evelina Fedorenko investigates how our brains process language. She has developed novel analytic approaches for functional magnetic resonance imaging (fMRI) and other brain imaging techniques to help answer the questions of how the language processing network functions and how it relates to other networks in the brain. She works with both neurotypical individuals and individuals with brain disorders. Fedorenko joins the Department of Brain and Cognitive Sciences as an assistant professor.