But in recent years, several clubs have brought boffins on board in the hopes of boosting their chances of success. Liverpool has partnered with Google's AI firm DeepMind to advise coaches on corner kicks, while other clubs have hired astrophysicists to analyse data and are even using missile-tracking technology to plot the move of every player. So, can science really tell us how to bend it like Beckham? MailOnline spoke to experts to uncover the formula for the winning football match ahead of Manchester United's match against Liverpool this Sunday. Can science really tell us how to bend it like Beckham? MailOnline spoke to experts to uncover the formula for the winning football match ahead of Manchester United's match against Liverpool this Sunday Taking a penalty is surely the most nerve-wracking experience for any player – a single moment that can decide the result of an entire tournament.

In this paper, we explore how techniques from soft robotics can help create a new form of robot expression. We present Sprout, a soft expressive robot that conveys its internal states by changing its body shape. Sprout can extend, bend, twist, and expand using fiber-embedded actuators integrated into its construction. These deformations enable Sprout to express its internal states, for example, by expanding to express anger and bending its body sideways to express curiosity. Through two user studies, we investigated how users interpreted Sprout's expressions, their perceptions of Sprout, and their expectations from future iterations of Sprout's design. We argue that the use of soft actuators opens a novel design space for robot expressions to convey internal states, emotions, and intent.

High-speed cameras have revealed how hummingbirds negotiate their way through tiny gaps while in flight, which happens much too quickly for the human eye to properly see. The findings could inform new techniques for flying robots. Hummingbirds feed on nectar and have to fly through tiny gaps in cluttered foliage as they flit from flower to flower. Marc Badger at the University of California, Berkeley, says it was while watching hummingbirds from his window that he decided to investigate how they achieve this. "When a dominant male would come and chase an intruder away, that intruder would fly through a bush," he says.

Every urban mobility EV concept needs some kind of fun gimmick, and Hyundai has delivered quite a few with its latest Mobis M.Vision concepts. The first model called the M.Vision POP is a small two seater not unlike Citroen's Ami, but with some unique features that make it much more tech-friendly and maneuverable. The POP was developed under Hyundai's "Tech Joy" theme, with a "core solution" called "Phobility." Translated from designer-speak, the idea is that your smartphone could not only be used to reserve a car, but would also be embedded in the steering wheel and "become the cockpit of the automobile itself," according to Hyundai. It can then interface with the vehicle's display, allow for voice recognition and "use smartphone sensors for wireless steering of the vehicle," somehow.

Increasingly, machine learning forms of artificial intelligence are contending with the limits of computing hardware, and it's causing scientists to rethink how they design neural networks. That was clear in last week's research offering from Google, called Reformer, which aimed to stuff a natural language program into a single graphics processing chip instead of eight. And this week brought another offering from Google focused on efficiency, something called Sideways. With this invention, scientists have borrowed a page from computer architecture, creating a pipeline that gets more work done at every moment. Most machine learning neural nets during their training phase use a forward pass, a transmission of a signal through layers of the network, followed by backpropagation, a backward pass through the same layers, only in reverse, to gradually modify the weights of a neural network till they're just right.

Children are the best examples when it comes to someone learning new things on their own. As whatever they learn is unsupervised and mostly learned by themselves without expecting rewards, children are the best teachers for artificial intelligence. Louisa May Alcott said, "I am not afraid of storms for I am learning to sail my ship." It seems like in today's era, artificial intelligence (AI) is sailing in the same boat with us. However, considering the recent advancements artificial intelligence is having, it looks like, it still has many things to learn before coming close to humans. When we say close to humans, many think about mimicking human behaviour, but that not really is the case.

In a park, perched on San Francisco's east bay, I set down Skydio's R1 drone, open an app on my phone, click "launch" and do something I would normally never do. I walk straight under a tree, knowing full well that the R1 will follow me and that the branches are directly in its flight path; I am trying to make it crash. I repeat this task a few more times, even with the drone flying backward but, try as I might, the R1 slips right under (and sometimes over) the tree's canopy. I am doing nothing but walking, no controller or phone in my hand; the R1 is figuring this all out by itself. Should I be surprised at this?

Pretty much every one on the plane threw up. Pilots were on the verge of throwing up." The members of the cleaning crew assigned to that wretched and retched-upon Bombardier regional jet were among the many victims of the Nor'easter currently slamming the East Coast. Winds as fierce as 70 mph have downed enough power lines to leave 450,000 in the dark, forced officials to suspend rail service and close bridges, and thrown planes about like a baby whacking the mobile above its crib. This kind of storm is no fun for anyone, except, maybe, the pilots.

Multicopter drones - drones with more than two rotors - are finally able to fly in any orientation. Normally, multicopter drones can only fly parallel to the ground, but a new hexacopter drone with six propellers can tilt 360 degrees, allowing it to fly in any orientation. The drone, dubbed Voliro, can fly sideways, upside down, diagonally and in other orientations. The Voliro was developed by a team of 11 students at the Swiss Federal Institute of Technology (ETH Zurich) and Zurich University of the Arts (ZHDK), who spent 9 months developing a prototype of the drone. Because the drone can stay stable while flying in any configuration, it's able to fly parallel to walls.

Using a familiar drag-and-drop interface, individuals can choose from a library of components and place them into the design. The tool suggests components that are compatible with each other, offers potential placements of actuators and can automatically generate structural components to connect those actuators. Once the design is complete, the tool provides a physical simulation environment to test the robot before fabricating it, enabling users to iteratively adjust the design to achieve a desired look or motion. "The process of creating new robotic systems today is notoriously challenging, time-consuming and resource-intensive," said Stelian Coros, assistant professor of robotics. "In the not-so-distant future, however, robots will be part of the fabric of daily life and more people -- not just roboticists -- will want to customize robots. This type of interactive design tool would make this possible for just about anybody."