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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.


Deep Learning in Robotics and Healthcare Summits: Join & save with KDnuggets offer

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RE•WORK are pleased to announce the launch of'Expo Only Passes' for the upcoming San Francisco events, on January 25 from 14:00 - 18:00. Plus, save 20% on passes to all RE•WORK summits with the code KDNUGGETS.


Can Artificial Intelligence Really Identify Suicidal Thoughts? Experts Aren't Convinced

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Australian experts have spoken out about a recent US study that claimed to show artificial intelligence can identify people with suicidal thoughts - by analysing their brain scans. It sounds promising - but it's worth pointing out only 79 people were studied, so are the results enough to show this is a path worth pursing? The research, published in Nature, studied brain activity in subjects when presented with a number of different words - like death, cruelty, trouble, carefree, good and praise. A machine-learning algorithm was then trained to see the nureal response differences between the two groups involved - those with suicidal thoughts, and those with non-suicidal thoughts. And it showed promise - the algorithm correctly identified 15 of 17 patients as belonging to the suicide group, and 16 of 17 healthy individuals as belonging to the control group.


Can Artificial Intelligence Really Identify Suicidal Thoughts? Experts Aren't Convinced

#artificialintelligence

Australian experts have spoken out about a recent US study that claimed to show artificial intelligence can identify people with suicidal thoughts - by analysing their brain scans. It sounds promising - but it's worth pointing out only 79 people were studied, so are the results enough to show this is a path worth pursing? The research, published in Nature, studied brain activity in subjects when presented with a number of different words - like death, cruelty, trouble, carefree, good and praise. A machine-learning algorithm was then trained to see the nureal response differences between the two groups involved - those with suicidal thoughts, and those with non-suicidal thoughts. And it showed promise - the algorithm correctly identified 15 of 17 patients as belonging to the suicide group, and 16 of 17 healthy individuals as belonging to the control group.


Brazilian banks lead in artificial intelligence planning

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Written on 17 November 2017. About 30 percent of local institutions see AI playing an important role in their innovation plans, according to GFT Technologies' Digital Banking Expert Survey. By comparison, 23 percent of sector firms in the UK and Mexico see AI as crucial in their strategy, while only 17 percent of US banks perceive the technology as an important aspect of their overall plans, the study from the financial services vendor says. The survey covered 285 professionals from small to large retail banks based in Brazil, Germany, Italy, Mexico, Spain, Switzerland, the UK and the US. Brazilian firms may be enthusiastic about the potential of artificial intelligence for tasks such as automating customer service and achieving greater customer engagement, but the country still struggles with issues ranging from infrastructure, lack of qualified manpower and effective partnerships with AI vendors and fintechs - that means the number of real initiatives is still small.


A global collaboration to create "artificial organisms" just went live

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Mindfire, a new foundation with the goal of "decoding the mind" to help develop true artificial intelligence (AI) is launching November 17th in Zurich, Switzerland. Futurism spoke with the founder of Starmind and president of the foundation, Pascal Kaufmann to learn more about its goals and the path to reach them. "We cannot achieve True AI until we understand actual intelligence. Intelligence has evolved as a means of nature to successfully guide us through an ever-changing environment. This gave rise to behavior, emotions, and consciousness.


Machine Learning A-Z : Hands-On Python & R In Data Science

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Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Includes: 40.5 hours on-demand video 20 Articles 2 Supplemental Resources Full lifetime access Access on mobile and TV Certificate of Completion Then this course is for you! This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way. We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.


Which Bugs Will Hackers Exploit First? Machine Learning Promises a Better Guess

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The vast majority of the bugs that hackers exploit aren't fancy zero-days that no one has ever seen or reported. Most are vulnerabilities that have gotten out into the wild and spread via chat rooms and hacker forums on the dark web. Guessing which bugs will cause the most damage -- useful in knowing which ones to patch first -- is still mostly a guess. But researchers from Arizona State University have developed a machine-learning model to predict which vulnerabilities are the most likely to cause the next headline-grabbing incident. Today's most common methods for anticipating the likelihood that a previously disclosed software vulnerability will cause major damage are imperfect at best.


Microsoft's Visual Studio gets new tools to help developers embrace AI

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Microsoft announced today that its Visual Studio integrated development environment is getting a new set of tools aimed at easing the process of building AI systems. Visual Studio Tools for AI is a package that's designed to provide developers with built-in support for creating applications with a wide variety of machine learning frameworks, like Caffe2, TensorFlow, CNTK, and MXNet. Once users have coded up models inside Visual Studio, the AI tools make it easier for them to send that code off to Microsoft's Azure cloud platform for training and deployment. Launching these tools brings a host of advanced capabilities to developers in a point-and-click format that would have previously required the use of a command line interface. It should make building AI systems more accessible for a class of developers that haven't been able to use Visual Studio's rich development environment to its full potential for that purpose.


Introduction to Machine Learning for Data Science

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Thank you all for the huge response to this emerging course! We are delighted to have over 300 students in over 145 different countries. I'm genuinely touched by the overwhelmingly positive and thoughtful reviews. It's such a privilege to share and introduce this important topic with everyday people in a clear and understandable way. I'm also excited to announce that I have created real closed captions for all course material, so weather you need them due to a hearing impairment, or find it easier to follow long (great for ESL students!)... I've got you covered.