big data


Managing the ethical complexities of the age of big data

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Governments have defined almost every conceivable aspect of property ownership. Can I cut down my neighbors' tree if it grows over my patio? Only those limbs that grow over the property line. Can I play music on my porch? Only if it doesn't interfere with your neighbor's enjoyment of their property.


Using drones, AI and big data, India to draw up digital map with 10 cms resolution India News - Times of India

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BENGALURU: India has initiated a project to digitally map the country with a resolution of 10 centimetres, using drones and technologies such as Artificial Intelligence and big data, a senior government official said on Monday. The herculean task was taken up by the Survey of India, part of the Department of Science and Technology, a few months ago and is planned to be completed in two years, the department's secretary, Prof Ashutosh Sharma said. "...now we are equipping them (Survey of India) with the latest technologies like drones, Artificial Intelligence, big data analytics, image processing and continuously operated reference system", he told reporters on the sidelines of an event here. Once the project is completed, the data will be available to citizens and to Gram Panchayats and local bodies, empowering them to use it in decision making and planning process. The survey is currently in progress in Karnataka, Haryana, Maharashtra and the Ganga basin.


Global Data Science Forum - Data Science

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The risks in the ML life cycle are also different since machine learning models have become pervasive in so many aspects of everyday consumer life – so much of which is tightly regulated. As machine learning models help automate important decisions in a wide variety of industries – banking, health care, airline schedules, telecom, shopping, entertainment, and so on – they become subject to much scrutiny about compliance, audits, needs for explainability, concerns about fairness and bias, privacy laws, security concerns, etc. Many of those activities are regulated, for important reasons. While more traditional software engineering similarly has security concerns, audits, etc., the stakes are not nearly as high: code can be debugged. Machine learning, especially when driven with large scale data, is substantially more difficult to trace and "debug" compared with coding.


University of Miami Deploys $3.7M IBM Power System for AI, HPC

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CORAL GABLES, Fla., August 13, 2019 – What if massive data sets could be accessed and analyzed in just an hour, instead of a day? It could change the field of genomics, help researchers predict impacts of climate change more expediently, and help understand the origins of the universe. Today, the University of Miami (UM) announced that their new supercomputer, Triton, is installed and helping their researchers and analysts explore these possibilities. The new high-performance system uses the same AI-optimized architecture as the most powerful supercomputers in the world, the U.S. Department of Energy's Summit and Sierra supercomputers. The $3.7 million system was assembled and validated distally by IBM and the University's Center for Computational Science (CCS) personnel.


How Robots Can Transform Retail With Machine Vision

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Robots have transcended the realm of sci-fi fantasy and are now making revolutionary waves in several industries. Industries that deal with complex, life-threatening tasks have been enjoying tremendous benefits from robots. From being controlled by a human operator to now being fully autonomous, robotics has vastly grown. Equipped with cutting-edge technologies, some robots today are designed such that they closely emulate human intelligence, in one form or another. Due to this, we see the use cases of robots in areas that need human intelligence and decision-making capabilities.


Nanning holds seminar on AI application in medicine

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A medical AI expert shares views from his experiences at the seminar. More than 30 local government representatives and experts in academic, medical, and industrial fields were invited to explore the pressing issues, pain points, and future development of artificial intelligence (AI) application in medicine in Nanning, Guangxi Zhuang autonomous region. Held by the Chinese Health Information and Big Data Association (CHIBDA) and the Big Data Development Bureau of Guangxi Zhuang Autonomous Region, the seminar aimed to promote the AI application in medical treatment. Participants conducted a discussion on the challenges encountered in the innovative cooperation of medical AI in its use, production, learning, and research, exploring the cooperation models between AI enterprises and hospitals from various perspectives. Combined with the local conditions in Guangxi, they also provided valuable experience and advice for the development of medical AI.


Webinar summary - Semantic annotation of images in the FAIR data era CGIAR Platform for Big Data in Agriculture

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Digital agriculture increasingly relies on the generation of large quantity of images. These images are processed with machine learning techniques to speed up the identification of objects, their classification, visualization, and interpretation. However, images must comply with the FAIR principles to facilitate their access, reuse, and interoperability. As stated in recent paper authored by the Planteome team (Trigkakis et al, 2018), "Plant researchers could benefit greatly from a trained classification model that predicts image annotations with a high degree of accuracy." In this third Ontologies Community of Practice webinar, Justin Preece, Senior Faculty Research Assistant Oregon State University, presents the module developed by the Planteome project using the Bio-Image Semantic Query User Environment (BISQUE), an online image analysis and storage platform of Cyverse.


Big data, big change

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Robots, in the past, were limited to performing some assigned prototype jobs by machines. These machines worked on preloaded instructions, and many were open-loop systems wherein, corrective measures were not included in the coded instructions. As the generations of robots are evolving, feedback systems with artificial intelligence (AI) have become an integral part for the robots. This new trend has resulted in a revolution in robotics which includes machine learning as a part of AI and robotics. Robotics is now not just limited to factories, industries and corporates to perform pre-assigned jobs, but have entered every aspect of life, including social life.


Big data, big change

#artificialintelligence

Robots, in the past, were limited to performing some assigned prototype jobs by machines. These machines worked on preloaded instructions, and many were open-loop systems wherein, corrective measures were not included in the coded instructions. As the generations of robots are evolving, feedback systems with artificial intelligence (AI) have become an integral part for the robots. This new trend has resulted in a revolution in robotics which includes machine learning as a part of AI and robotics. Robotics is now not just limited to factories, industries and corporates to perform pre-assigned jobs, but have entered every aspect of life, including social life.


Cartoon: Unsupervised Machine Learning?

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New KDnuggets Cartoon looks at unsupervised Machine Learning, which is considered by many leading AI researchers to be the next frontier in AI. This cartoon looks at the situation when Machine Learning becomes too unsupervised. This cartoon was ably drawn by Jon Carter. See also other recent KDnuggets Cartoons: Cartoon: AI and March Madness Cartoon: Is this how you do the blockchain thing? Cartoon: Where AI achieves excellence Cartoon: Machine Learning takes a vacation Cartoon: Data Scientist was the sexiest job of the 21st century until ... Cartoon: How is Data Science Different From Religion?