Researchers at the Massachusetts Institute of Technology have developed an'intelligent' carpet that can sense human movement and poses without using cameras, opening up a whole new world in both gaming and health care. At this week's Conference on Computer Vision and Pattern Recognition, a team from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) demonstrated a 36' by 2' mat than can extrapolates the sitter's posture, movement and relationship to the ground in a 3D model. If a user steps onto the mat and performs a sit up, the system can produce an image of a figure doing a sit up. The mat is trained on synchronized tactile and visual data, such as video footage and a heatmap of a volunteer doing a sit up or pushup. Researchers at MIT are working on a mat embedded with thousands of sensors that can detect pressure from feet, limbs and other body parts.

"Robot design is still a very manual process. RoboGrammar is a way to come up with new, more inventive robot designs." The way humans move effortlessly can obscure them of the complex motions of the joints and limbs. One would be shocked if they were to build a robot considering all the degrees of freedom, the weight of the payload, 3D geometry and more. The sophisticated designs of robots have been more or less the same.

Researchers at MIT have developed a new method of navigation for robots that could be very useful for the range of companies working on autonomous last-mile delivery. In short, the team has worked out how a robot can figure out the location of a front door, without being provided a specific map in advance. Most last-mile autonomous delivery robots today, including the "wheeled cooler"-style variety that was pioneered by Starship and has since been adopted by a number of other companies, including Postmates, basically meet customers at the curb. Mapping isn't the only barrier to having future delivery bots go all the way to the door, just like the humans who make those deliveries today. MIT News points out that mapping an entire neighborhood with the level of specificity required to do true front-door delivery would be incredibly difficult -- particularly at national (let alone global) scale.

Picking stuff up seems easy, right? It is – for humans with powerful brain computers that instantly and intuitively figure out everything needed to get the job done. But for robots, even advanced robots, the compute required is surprisingly complex, especially if you want the robot to not, you know, break the thing it's grabbing. MIT has developed a new way to speed up the planning involved in a robot grasping an object, making it "significantly" faster – reducing the total time from as much as ten or more minutes, to under a second. This could have big practical benefits to setting where robotics are already in use, including in industrial environments.

Researchers at MIT have developed a new hardware chip that can make neural networks in smart devices more power efficient. Usually, neural networks require much energy as they are computing a large of data at once, so while there are neural features on devices such as smartphones, they are integrated on a smaller scale. The data is usually is sent to the web instead to process all the information and sent back to the device. However, these chips compute information three to seven times faster than currently dedicated chips. Not only that, they reportedly consume 94 to 95 percent less power, making them an idea inclusion on smaller handheld devices in the future.

MIT announced today that it's developed a speech recognition chip capable of real world power savings of between 90 and 99 percent over existing technologies. Voice technology has, of course, become nearly ubiquitous in mobile devices, thanks to the exponential growth of smart assistants like Siri, Alexa and Google Home – but the new chip could help branch out in much simpler electronics. The team gives IoT devices a potential use case – devices designed to go months on end without charging or changing batteries. Speech input will become a natural interface for many wearable applications and intelligent devices. The miniaturization of these devices will require a different interface than touch or keyboard.

A superhero who was able to see two seconds into the future wouldn't be invincible, but she'd have a leg up on mere mortals. On Monday, the Massachusetts Institute of Technology announced its new artificial intelligence, and it's a prototype of such a being. Based on a photograph alone, it can predict what'll happen next, then spit out a one-and-a-half second video clip depicting that possible future. The breakthrough could yield smarter autonomous cars or security systems. MIT researchers trained the A.I. by feeding over two million videos into its two-pronged deep-learning system.