Technological advances like artificial intelligence, machine learning and big data are impacting the power sector as well, making it imperative for producers to re-skill resources, a senior official of Tata Power said. "With technological disruptions like artificial intelligence, machine learning, big data, augmented reality etc. that are impacting the power sector as well, it has become imperative to re-train and re-skill resources for emerging careers where the demand is more than the supply," Tata Power Chief Human Resource Officer Jayant Kumar said. Addressing the seventh Power HR Round Table organised by the University of Petroleum & Energy Studies (UPES), Kumar said, "Curiosity, courage and comfort with technology are the traits of a future digital worker." CEOs and HR heads of leading Indian companies in the power sector such as Tata Power, Power Grid, GMR Energy, Adani Green Energy, and DB Power deliberated on various challenges faced by the sector today and possible solutions, UPES said in a statement. "Power distribution companies (Discoms), due to their nature of work, have access to huge consumer data and they can use this data to foray into other allied businesses just the way cab aggregators are delivering food or e-commerce companies providing video-on-demand services," Ashis Basu, CEO (Corporate), GMR Energy, suggested.
The School of Engineering has announced the addition of 16 new faculty members to its departments, institutes, labs, and centers during the 2017-18 and 2018-19 academic years. With research and teaching activities ranging from personalization in the microbiome to the application of machine learning to naval architecture, they are poised to make vast contributions in new directions across the school and to a range of labs and centers across the Institute. "I am pleased to welcome our exceptional new faculty. Their presence will enhance the breadth and depth of education and research within the School of Engineering, and strengthen MIT's commitment to making a better world," says Anantha Chandrakasan, dean of the School of Engineering. "I look forward to their contributions in the years to come."
The idea of man-made artificial intelligence is something that has fascinated and puzzled scientists, engineers and philosophers since the middle of the 20th century. Today, amid news that China and the United States are engaged in a race for AI superiority, and major progress by companies such as Google in making AI a reality, philosophical debates continue. This week, researchers gathered in Long Beach, California for the Neural Information Processing Systems Conference to discuss the possible dangers relating to the growing power of AI, and how to imbue it with an'ethical conscience.' Those subscribing to the first view fear the unknown, and what thoughts may appear in the AI's virtual mind. Scientists, meanwhile, for the most part, are more prone to supporting the latter.
Sarcos Robotics, a Salt Lake City-based robotics company, has three new products at market or debuting soon. One is a small robotic snake, useful for industrial tasks such as pipeline inspection or for first responders conducting search & rescue or tactical response operations. Another is a hulking two-armed tele-operated robot that can be used for heavy construction or in nuclear power plants. The third is an exoskeleton suit that allows workers to nimbly perform the functions of a forklift. The technology is cool and worthy of the recent spate of coverage.
"We're not in an environment that allows us to agree to the restarts of the reactors, in view of persistent concern among the residents of our prefecture," Mikazuki said at a meeting with Masaharu Nakagawa, minister for nuclear emergency preparedness, in Otsu, Shiga's capital. Nakagawa had been visiting to brief the governor on evacuation plans for a severe accident at the Oi plant. Mikazuki was speaking up because part of Takashima, Shiga Prefecture, is included in the so-called urgent protective action planning zone (UPZ) that lies within 30 km of the plant, which is in Fukui. Kansai Electric is aiming to reboot the two Oi reactors early next year. On the Oi plant's evacuation plans, Mikazuki pointed to the absence of plans for residents, as well as the challenge of securing rescue vehicles and drivers.
On November 7, China announced plans to open an unmanned police station powered by artificial intelligence (AI) in Wuhan, one of its capital cities. The AI police station will likely focus on vehicle- and driver-related issues, which makes it more analogous to an American Department of Motor Vehicles (DMV) than a precinct (sorry, Robocop), but the decision to build it is still right inline with China's plans to be a world leader in AI by 2030. According to a report from the Chinese financial paper Caijing Neican, the futuristic station will offer simulated driver examinations and provide registration services. Cutting-edge facial-recognition technology developed by Tencent will identify citizens within the station. The idea is that this will eliminate the need for users to sit at stations for long periods of time, sign up for accounts, or download apps -- the AI will access all pertinent information as soon as it sees the person's face.
Engineers at Purdue University in Lafayette, Indiana are developing a new system for keeping nuclear reactors safe with artificial intelligence (AI). In the paper published in the IEEE Transactions on Industrial Electronics journal, the researchers introduced a deep learning framework called a naïve Bayes-convolutional neural network that can effectively identify cracks in reactors by analyzing individual video frames. The method could potentially make safety inspections safer. "Regular inspection of nuclear power plant components is important to guarantee safe operations," Mohammad Jahanshahi, an assistant professor at Purdue's Lyles School of Civil Engineering, said in a press release. "However, current practice is time-consuming, tedious, and subjective and involves human technicians reviewing inspection videos to identify cracks in reactors."
Intelligence agencies have a limited number of trained human analysts looking for undeclared nuclear facilities, or secret military sites, hidden among terabytes of satellite images. But the same sort of deep learning artificial intelligence that enables Google and Facebook to automatically filter images of human faces and cats could also prove invaluable in the world of spy versus spy. An early example: US researchers have trained deep learning algorithms to identify Chinese surface-to-air missile sites--hundreds of times faster than their human counterparts. The deep learning algorithms proved capable of helping people with no prior imagery analysis experience find surface-to-air missile sites scattered across nearly 90,000 square kilometers of southeastern China. Such AI based on neural networks--layers of artificial neuron capable of filtering and learning from huge amounts of data--matched the overall 90 percent accuracy of expert human imagery analysts in locating the missile sites.