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Experimental drone uses AI to spot violence in crowds. Whether or not it works well in practice is another story. Drone-based surveillance still makes many people uncomfortable, but that isn't stopping research into more effective airborne watchdogs. Scientists have developed an experimental drone system that uses AI to detect violent actions in crowds. The team trained their machine learning algorithm to recognize a handful of typical violent motions (punching, kicking, shooting and stabbing) and flag them when they appear in a drone's camera view. The technology could theoretically detect a brawl that on-the-ground officers might miss, or pinpoint the source of a gunshot. As The Verge warned, the technology definitely isn't ready for real-world use. The researchers used volunteers in relatively ideal conditions (open ground, generous spacing and dramatic movements). The AI is 94 percent effective at its best, but that drops down to an unacceptable 79 percent when there are ten people in the scene. As-is, this system might struggle to find an assailant on a jam-packed street -- what if it mistakes an innocent gesture for an attack? The creators expect to fly their drone system over two festivals in India as a test, but it's not something you'd want to rely on just yet. There's a larger problem surrounding the ethical implications. There are questions about abuses of power and reliability for facial recognition systems. Governments may be tempted to use this as an excuse to record aerial footage of people in public spaces, and could track the gestures of political dissidents (say, people holding protest signs or flashing peace symbols). It could easily combine with other surveillance methods to create a complete picture of a person's movements. This might only find acceptance in limited scenarios where organizations both make it clear that people are on camera and with reassurances that a handshake won't lead to police at their door. Content gathered by BTM robotics training center, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP nagar, robotics training centers in Bannerghatta road, robotics training centers in JP nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore.
Nvidia is training robots to learn new skills by observing humans. Initial experiments with the process have seen a Baxter robot learn to pick up and move colored boxes and a toy car in a lab environment. The researchers hope the development of the new deep-learning based system will go some way to train robots to work alongside humans in both manufacturing and home settings. “In the manufacturing environment, robots are really good at repeatedly executing the same trajectory over and over again, but they don’t adapt to changes in the environment, and they don’t learn their tasks, ” Nvidia principal research scientist Stan Birchfield told VentureBeat. “So to repurpose a robot to execute a new task, you have to bring in an expert to reprogram the robot at a fairly low level, and it’s an expensive operation. What we’re interested in doing is making it easier for a non-expert user to teach a robot a new task by simply showing it what to do.” The researchers trained a sequence of neural networks to perform duties associated with perception, program generation, and program execution. The result was that the robot was able to learn a new task from a single demonstration in the real world. Once the robot witnesses the task, it generates a human-readable description of the states required to complete the task. A human can then correct the steps if necessary before execution on the real robot. “There’s sort of a paradigm shift happening in the robotics community now, ” Birchfield said. “We’re at the point now where we can use GPUs to generate essentially a limitless amount of pre-labeled data essentially for free to develop and test algorithms. And this is potentially going to allow us to develop these robotics systems that need to learn how to interact with the world around them in ways that scale better and are safer.” In a video released by the researchers, human operator shows a pair of stacks of cubes to the robot. The system then understands an appropriate program and correctly places the cubes in the correct order. Information gathered by - Robotics for u. Bangalore Robotics, BTM Robotics training center, Robotics spares, Bannerghatta Robotics training center, best robotics training in bangalore,
Controlling robots with brainwaves and hand gestures Computer Science and Artificial Intelligence Laboratory system enable people to correct robot mistakes on multiple-choice tasks. Getting robots to do things isn’t easy, usually, scientists have to either explicitly program them or get them to understand how humans communicate via language. But what if we could control robots more intuitively, using just hand gestures and brainwaves? A new system spearheaded by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) aims to do exactly that, allowing users to instantly correct robot mistakes with nothing more than brain signals and the flick of a finger. Building off the team’s past work focused on simple binary-choice activities, the new work expands the scope to multiple-choice tasks, opening up new possibilities for how human workers could manage teams of robots. By monitoring brain activity, the system can detect in real-time if a person notices an error as a robot does a task. Using an interface that measures muscle activity, the person can then make hand gestures to scroll through and select the correct option for the robot to execute. Content gathered by BTM robotics training center, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP nagar, robotics training centers in Bannerghatta road, robotics training centers in JP nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore,
Nvidia 's AI makes a breakthrough in ray tracing(computer graphics): Nvidia' AI that started out in 2017 as something that was not expected to do as much as it has already done like enriching graphics, transforming huge amounts of medical data into life saving breakthroughs, identifying diseases with a simple drop of blood, finding new ways to bring cures to the market faster, helping crops to flourish with optimal materials, customer assistance, self driving vehicles, analysis of various things in search for solutions etc. This AI became popular due to the Isaac robot simulator program. This got rid of programming and let the AI or robot think and learn on its own. Of course initially it was inefficient but after they found out that the robot could successfully learn something like hockey they wanted to make it efficient. This is where their idea of a virtual world comes in. They crated a program that takes the brain of a robot and puts it in a virtual world where it is allowed to try as much as it likes to achieve a certain task. This virtual world follows the laws of our world except for time. In this world a robot can practice its goal in very less time therefore becoming efficient. This AI has now made a breakthrough in computer graphics. ray tracing which is a method used for non real time instances due to its low computing speed has now been turned into a more faster computing one to handle real time gaming systems. Ray tracing is normally used to enhance effects bye understanding how our eye works, but was unable to handle on going instances like gaming and that was why it was limited to only movies.But now thanks to the AI and the quadro GV100 it is now possible to use get high quality graphics by using ray tracing for games as well. This also cuts the cost to 1/5 the original and takes 1/7 the original time taken. Issued by BTM layout robotic center
Researchers build a self-healing 'robot skin'. Puncture a hole, and the alloy will fill in the gap. Most conventional androids are fairly rigid, susceptible to damage and difficult to repair. However, scientists are determined to (literally) give them thicker skins. They've experimented with soft, deformable circuits that are flexible, and could reduce business expenses in the long term -- but are still prone to tearing and puncturing. The solution to these issues may lie in one recent advancement. A group of researchers from Carnegie Mellon University have found a way to counter surface damage and electrical failure commonly observed in soft materials used in engineering robotic electronics. Like previous efforts, it involves a certain kind of polymer. To create a material that is both flexible and resistant to damage, Carmel Majidi and his team inserted liquid micro droplets of a gallium-indium based metal alloy into a soft, elastomer shell. Essentially, it's a solid-liquid hybrid that is stretchable, electrically insulating and capable of auto-repair even when damaged multiple times. Where most other self-healing soft electronics need exposure to heat, increased humidity or manual reassembly to get back to health, the metal-elastomer composite heals itself by forming new electrical pathways. Majidi says the inspiration behind the composite material comes from the nervous system's ability to regenerate itself. It isn't mimicking neuroplasticity entirely, though; while the metal-elastomer could be useful in wearable computing and inflatable airships to protect electrical wiring from potential damage, there's no such protection for mechanical or structural damage. That's the eventual aim -- creating a material which helps robots weather both electrical and structural defects and, like Astro Boy, interact with humans more safely. Content gathered by BTM robotics training center, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP nagar, robotics training centers in Bannerghatta road, robotics training centers in JP nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore.
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