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SAY HI TO CIMON, THE FIRST AI-POWERED ROBOT TO FLY IN SPACE. When you thought that Artificial Intelligence (AI) is redefining life on Earth, think again! Meet CIMON, the first AI-powered robot who was launched into space from Florida on Friday, June 29th to join the crew and assist astronauts of the International Space Station (ISS). CIMON was launched by a SpaceX rocket carrying food and supplies for the crew aboard the International Space Station. At CIMON’s pre-launch news conference, Kirk Shireman, NASA’s International Space Station (ISS) program manager, addressed that the knowledge base and ability to tap into AI in a way that is useful for the task that is done is really critical for having humans further and further away from the planet. CIMON or (Crew Interactive Mobile Companion) is programmed to answer voice commands in English. The AI-powered robot is roughly the size of a volleyball and weighs 5 kilograms. CIMON will float through the zero-gravity environment of the space station to research a database of information about the ISS. In addition to the mechanical tasks assigned, the AI-powered CIMON can even assess the moods of its human crewmates at the ISS and interact accordingly with them. An Intelligent Astronaut CIMON is the brainchild of the European aerospace company Airbus. With the artificial intelligence inside powered by IBM, AI-Powered CIMON was initially built for the German space agency. Alexander Gerst, a German astronaut currently aboard the ISS, assisted with the design of CIMON’s screen prompts and vocal controls. As per the mission description written by Airbus representatives, CIMON’s mission calls for the AI-Powered astronaut robot to work with Gerst on three separate investigations. Cimon’s tasks at ISS include experimenting with crystals, working together with Gerst to solve the Rubik’s cube and performing a complex medical experiment using itself as an ‘intelligent’ flying camera. CIMON can interact with anyone at ISS; the AI-powered robot will nod when any command is spoken in English. However, CIMON is programmed to specifically help Gerst during its first stay on the ISS. Alexander Gerst can make CIMON work by speaking commands in English like, ‘CIMON, could you please help me perform a certain experiment? or could you please help me with the procedure?'” In response, CIMON will fly towards Alexander Gerst, to start the communication. An Interactive Step Forward CIMON knows whom it is talking to through its inbuilt facial-recognition software. If you thought that CIMON would look like a mechanical robot, you are wrong. CIMON has a face of its own, a white screen with a smiley face. The astronaut AI assistant will be able to float around, by sucking air in and expelling it out through its special tubes once it is aboard the ISS. CIMON’s mission to space demonstrates researchers, the collaboration of humans and AI-powered technology for further explorations. However, it will be a long way before intelligent robots are ready to undertake principal tasks in the final frontier including helping astronauts repair damaged spacecraft systems or treating sick crewmembers. But a beginning has been made with CIMON and that day will probably be a reality soon. In its first space mission, CIMON will stay in space for a few months and is scheduled to return to earth in December. Post its return, scientists will study and assess its abilities for future implementations. With the launch of CIMON, a lifelong space-exploration association between humans and machine may have just begun. Content gathered by BTM robotics training centre, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP Nagar, robotics training centres in Bannerghatta road, robotics training centres in JP Nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore.
'Blind' Cheetah 3 robot can climb stairs littered with obstacles. MIT's Cheetah 3 robot can now leap and gallop across rough terrain, climb a staircase littered with debris, and quickly recover its balance when suddenly yanked or shoved, all while essentially blind. The 90-pound mechanical beast -- about the size of a full-grown Labrador -- is intentionally designed to do all this without relying on cameras or any external environmental sensors. Instead, it nimbly "feels" its way through its surroundings in a way that engineers describe as "blind locomotion, " much like making one's way across a pitch-black room. "There are many unexpected behaviours the robot should be able to handle without relying too much on vision, " says the robot's designer, Sangbae Kim, associate professor of mechanical engineering at MIT. "Vision can be noisy, slightly inaccurate, and sometimes not available, and if you rely too much on vision, your robot has to be very accurate in position and eventually will be slow. So we want the robot to rely more on tactile information. That way, it can handle unexpected obstacles while moving fast." Researchers will present the robot's vision-free capabilities in October at the International Conference on Intelligent Robots, in Madrid. In addition to blind locomotion, the team will demonstrate the robot's improved hardware, including an expanded range of motion compared to its predecessor Cheetah 2, that allows the robot to stretch backwards and forwards, and twist from side to side, much like a cat limbering up to pounce. Within the next few years, Kim envisions the robot carrying out tasks that would otherwise be too dangerous or inaccessible for humans to take on. "Cheetah 3 is designed to do versatile tasks such as power plant inspection, which involves various terrain conditions including stairs, curbs, and obstacles on the ground, " Kim says. "I think there are countless occasions where we [would] want to send robots to do simple tasks instead of humans. Dangerous, dirty, and difficult work can be done much more safely through remotely controlled robots." Making a commitment The Cheetah 3 can blindly make its way up staircases and through unstructured terrain, and can quickly recover its balance in the face of unexpected forces, thanks to two new algorithms developed by Kim's team: a contact detection algorithm, and a model-predictive control algorithm. The contact detection algorithm helps the robot determine the best time for a given leg to switch from swinging in the air to stepping on the ground. For example, if the robot steps on a light twig versus a hard, heavy rock, how it reacts -- and whether it continues to carry through with a step, or pulls back and swings its leg instead -- can make or break its balance. "When it comes to switching from the air to the ground, the switching has to be very well-done, " Kim says. "This algorithm is really about, 'When is a safe time to commit my footstep?'" The contact detection algorithm helps the robot determine the best time to transition a leg between swing and step, by constantly calculating for each leg three probabilities: the probability of a leg making contact with the ground, the probability of the force generated once the leg hits the ground, and the probability that the leg will be in midswing. The algorithm calculates these probabilities based on data from gyroscopes, accelerometers, and joint positions of the legs, which record the leg's angle and height with respect to the ground. If, for example, the robot unexpectedly steps on a wooden block, its body will suddenly tilt, shifting the angle and height of the robot. That data will immediately feed into calculating the three probabilities for each leg, which the algorithm will combine to estimate whether each leg should commit to pushing down on the ground, or lift up and swing away in order to keep its balance -- all while the robot is virtually blind. "If humans close our eyes and make a step, we have a mental model for where the ground might be, and can prepare for it. But we also rely on the feel of touch of the ground, " Kim says. "We are sort of doing the same thing by combining multiple [sources of] information to determine the transition time." The researchers tested the algorithm in experiments with the Cheetah 3 trotting on a laboratory treadmill and climbing on a staircase. Both surfaces were littered with random objects such as wooden blocks and rolls of tape. "It doesn't know the height of each step and doesn't know there are obstacles on the stairs, but it just ploughs through without losing its balance, " Kim says. "Without that algorithm, the robot was very unstable and fell easily." Future force The robot's blind locomotion was also partly due to the model-predictive control algorithm, which predicts how much force a given leg should apply once it has committed to a step. "The contact detection algorithm will tell you, 'this is the time to apply forces on the ground, '" Kim says. "But once you're on the ground, now you need to calculate what kind of forces to apply so you can move the body in the right way." The model-predictive control algorithm calculates the multiplicative positions of the robot's body and legs a half-second into the future if a certain force is applied by any given leg as it makes contact with the ground. "Say someone kicks the robot sideways, " Kim says. "When the foot is already on the ground, the algorithm decides, 'How should I specify the forces on the foot? Because I have an undesirable velocity on the left, so I want to apply a force in the opposite direction to kill that velocity. If I apply 100 newtons’s in this opposite direction, what will happen a half second later?" The algorithm is designed to make these calculations for each leg every 50 milliseconds, or 20 times per second. In experiments, researchers introduced unexpected forces by kicking and shoving the robot as it trotted on a treadmill, and yanking it by the leash as it climbed up an obstacle-laden staircase. They found that the model-predictive algorithm enabled the robot to quickly produce counter-forces to regain its balance and keep moving forward, without tipping too far in the opposite direction. "It's thanks to that predictive control that can apply the right forces on the ground, combined with this contact transition algorithm that makes each contact very quick and secure, " Kim says. The team had already added cameras to the robot to give it visual feedback of its surroundings. This will help in mapping the general environment and will give the robot a visual heads-up on larger obstacles such as doors and walls. But for now, the team is working to further improve the robot's blind locomotion "We want a very good controller without vision first, " Kim says. "And when we do add vision, even if it might give you the wrong information, the leg should be able to handle (obstacles). Because what if it steps on something that a camera can't see? What will it do? That's where blind locomotion can help. We don't want to trust our vision too much." This research was supported, in part, by Naver, Toyota Research Institute, Foxconn, and Air Force Office of Scientific Research. 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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,
New giant drones are strong enough to perform jobs such as cleaning wind turbines, fighting fires and even carrying people to safety. Some of the dirtiest, most dangerous jobs are being taken over by artificial intelligence, robots, and drones. Machines are slowly becoming man’s best friend, helping us do tough, risky, or menial tasks. Future drones will do more than just peruse the skies, surveying and filming. New innovations in drone technology show their potential to take on much larger tasks that benefit society in new ways. New giant drones are now capable of cleaning wind turbines, fighting fires, and even carrying people to safety. An innovative startup, Aeron, has built a giant drone equipped with 28 motors and 16 batteries. The stout prototypes can lift up to 400 pounds, potentially rescuing people from burning buildings. In a series of videos, the founders demonstrate how the new drones can manoeuvre with hoses to clean and de-ice wind turbines. These large quadcopters can manoeuvre alongside tall buildings, clean the windows, or put out a potential fire.The ambitious startup, backed by Y Combinator, is already getting orders from around the world to help clean and de-ice wind turbines. The greatest challenge for these new drones is sustaining power. Relying on battery only, these drones can only carry a load for about twelve minutes. For now, the drones are better off tethered and connected to a power source from the ground. As the capability of drones expands, the implications for abuse become more real, too. A drone that can rescue people from fires can also identify, locate, and displace a person for various reasons. Large drones of this nature could be used to protect property, locating and removing threats from private areas. Who will make the rules that govern how drones can and cannot be used? A large drone that fights fires can also fight insurrection, threaten protestors, or spray down mobs. In the eyes of authority, this could be seen as a good use for drones, to curb violence; however, the power could readily be abused. Government forces could use drones in an authoritarian, intimidating manner, threatening peaceful assembly, free speech, and democracy. Drones equipped with tear gas could help riot police disperse their opposition. Large drones could easily be used as a means of force to control others. (Related: Drone makers looking to expand into civilian law enforcement market as a replacement for police helicopters.) A giant drone that can operate hoses to clean wind turbines also has the capability to operate hoses to fumigate from overhead. If a city council declared that a vector-borne disease was threatening their community, they could deploy these large drones overhead to fumigate mosquitoes and ticks in certain areas. The residents of the city will have no control over the operation or the number of nervous system toxins that are being sprayed into the air. That same drone could be used to spray disinfectants over an area that has been declared an outbreak zone. Health officials, paying no mind to the consequences of spraying people with biological agents and other chemicals, could experiment with airborne flu vaccines to combat a declared flu outbreak. As drone capabilities expand, it won’t be long before authorities begin using the technology to their advantage. It will be much easier for authorities to carry out force if they can hide behind the technology. 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.
Demand for Artificial intelligence & robotics experts to be higher by 50-60% in 2018 Artificial intelligence (AI) is the buzz in the jobs bazaar as machine learning and the Internet of Things (IoT) increasingly influence business strategies and analytics. Human resource and search experts estimate a 50-60% higher demand for AI and robotics professionals in 2018 even as machines take over repetitive manual work. “Machines are taking over repetitive tasks. Robotics, AI, big data, and analytics will be competencies that will be in great demand, ” said Shakun Khanna, senior director at Oracle for the Asia-Pacific region. Organizations are being pushed to become even more efficient as jobs turn predictable, said Rishabh Kaul, co-founder of recruitment startup Belong, which helps clients search for and hire AI professionals. “There is a significant increase in the adoption of AI and automation across enterprises, leading to a skyrocketing of demand for professionals in these fields, ” he said. Jobs in the IoT ecosystem have grown fourfold in the last three years, according to estimates by Belong. These are related to engagement technologies and data capture among other areas. Demand for professionals in the realm of data analysis, including data scientists, has grown by almost 76% in the past few years in AI. The demand is at the entry level as well as middle to senior ranks across sectors such as business, financial services and insurance (BFSI), e-commerce, startups, business process outsourcing (BPO), information technology (IT), pharmaceuticals, healthcare, and retail. “Robotics is required by process-oriented companies for a better customer experience. It helps in cutting down cost and improves efficiency, ” said Thammaiah BN, managing director, Kelly Services India. “AI is helping companies to be in spaces so far not thought of. Organizations can accomplish new things, new products, and services through AI.” Companies want to mine the data they have accumulated over the years, said Sinosh Panicker, partner, Hunt Partners. “AI helps them predict and position their products better and push out new things, ” he said. However, there’s an acute demand-supply mismatch for AI talent across industries, experts said. Candidates for AI roles related to natural language processing (NLP), deep learning, and machine learning are thin on the ground, according to the Belong Talent Supply Index. The ratio of the number of people to jobs in deep learning is 0.53, while for machine learning it’s 0.63 and for NLP it’s 0.71. Only 4% of AI professionals in India have worked on cutting-edge technologies such as deep learning and neural networks, the key ingredients in building advanced AI-related solutions, said Kaul. A few academic institutions such as the Indian Institutes of Technology (IITs) in Kharagpur and Kanpur, the Indian Institute of Information Technology (IIIT) in Hyderabad and the Indian Institute of Science (IISc) in Bengaluru have specialized disciplines or centres for artificial intelligence and machine learning. “In fact, according to our internal research, less than 2% of professionals who call themselves data scientists or data engineers have a PhD in AI-related technologies, ” said Kaul. Such is the need for talent that it is prompting top business schools, including the Indian Institutes of Management (IIMs), to include AI and machine learning in their curriculum and expose students to the full ecosystem of IoT. The IIMs in Bangalore and Kozhikode and premier B-Schools like the SP Jain Institute of Management & Research (SPJIMR) are offering courses on AI, robotics, and IoT that can be connected to business strategy to enhance performance, output and customer experience. Some are learning skills through various other courses, including online ones. “People who are keeping themselves abreast with new age technologies and have the right set of required skills under the same are in high demand, ” said ABC Consultants director Ratna Gupta. Content gathered by BTM robotics training centre, robotics in Bangalore, stem education in Bangalore, stem education in Bannerghatta road, stem education in JP Nagar, robotics training centres in Bannerghatta road, robotics training centres in JP Nagar, robotics training for kids, robotics training for beginners, best robotics in Bangalore,