Utilities


Artificial Intelligence: What to Expect From Smart Hardware?

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By the mid-20th century, both physicists and lyricists were scratching their heads over the issue of artificial intelligence. What would it be like? What kinds of risks would it bear for humanity? Now we know the answer to the first question. Artificial intelligence is a computer program.


School of Engineering welcomes new faculty

MIT News

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."


This is the smartest robotics company in the world (and soon to be one of the most important)

ZDNet

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.


Citing lack of evacuation plans, Shiga governor repeats objections to Oi reactor restarts

The Japan Times

"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.


How artificial intelligence is making nuclear reactors safer

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The deep learning framework can effectively identify cracks in nuclear reactors by analyzing individual video frames.


How artificial intelligence is making nuclear reactors safer

#artificialintelligence

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."


Artificial Intelligence Can Hunt Down Missile Sites in China Hundreds of Times Faster Than Humans

WIRED

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.


System uses 'deep learning' to detect cracks in nuclear reactors - Purdue University

@machinelearnbot

WEST LAFAYETTE, Ind. – A system under development at Purdue University uses artificial intelligence to detect cracks captured in videos of nuclear reactors and represents a future inspection technology to help reduce accidents and maintenance costs. "Regular inspection of nuclear power plant components is important to guarantee safe operations," said Mohammad R. Jahanshahi, an assistant professor in Purdue's Lyles School of Civil Engineering. "However, current practice is time-consuming, tedious, and subjective and involves human technicians reviewing inspection videos to identify cracks on reactors." Complicating the inspection process is that nuclear reactors are submerged in water to maintain cooling. Consequently, direct manual inspection of a reactor's components is not feasible due to high temperatures and radiation hazards.


A.I. system finds cracks in nuclear reactors - Futurity

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You are free to share this article under the Attribution 4.0 International license. A new system that uses artificial intelligence to find cracks captured in videos of nuclear reactors could help reduce accidents as well as maintenance costs, researchers report. "Regular inspection of nuclear power plant components is important to guarantee safe operations," says Mohammad R. Jahanshahi, an assistant professor in the Lyles School of Civil Engineering at Purdue University. "However, current practice is time-consuming, tedious, and subjective and involves human technicians reviewing inspection videos to identify cracks on reactors," Jahanshahi says. The fact that nuclear reactors are submerged in water to maintain cooling complicates the inspection process.


The robot that could help clean up Fukushima

Daily Mail

From Fukushima in Japan to Sellafield in the UK, the world is home to a number of sites that are contaminated with radioactive waste and require clean-up. The current techniques available to do this are expensive and time consuming – but a new'super hero' robot could help to cut both costs and time. The robot, called Avexis, is designed to fit through a 100mm access port in the flooded reactors at the Fukushima site, to locate and analyse melted fuel. Many areas around Fukushima are still being decontaminated, 58,000 people are still displaced from their homes and the local food industries have been crippled. Its designers hope that the robot will be ready to deploy at the Fukushima Daiichi Nuclear power plant by February 2018.