Welcome to the July 14, 2017 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Forecasting How Humans Will Interact With Machines by 2030
eWeek
Chris Preimesberger
July 12, 2017
A new study by Dell Technologies, the Institute for the Future, and 20 global experts examined the potential nature of relationships among humans, machines, and new technologies by 2030. The study predicts that advancements in software, big data, and processing power will reshape people's relationship with machines. For example, humans will serve as "digital conductors" in which technology will work as an extension of people, helping to better direct and manage daily activities. The pace of change by 2030 will be so rapid that new industries will be created and new skills will be required to survive. Personalized, integrated artificial intelligence assistants will take care of people in predictive and automated ways. The study also forecasts that work will cease to be a place but instead become a series of tasks. Machine-learning technologies will make individuals' skills and competencies searchable, and organizations will pursue the best talent for discrete tasks.
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Why You Might Trust a Quantum Computer With Secrets
Center for Quantum Technologies (Singapore)
July 12, 2017
Researchers at the Center for Quantum Technologies (CQT) at the National University of Singapore and the Singapore University of Technology, along with colleagues at RMIT University in Australia, have developed a new scheme that brings secrecy to a form of quantum computing that is driven by measurements. In the new scheme, the quantum computer is prepared by putting all of its qubits into a special type of entangled state. Measuring the qubits one by one then completes the computation. Although researchers have previously shown that users who can make or measure qubits to convey instructions to the quantum computer could disguise their computation, the new research extends that power to users who can only send classical bits. "You can use this unique feature of the measurement-based model of quantum computing--the way information flows through the state--as a crypto tool to hide information from the server," says CQT researcher Tommaso Demarie.
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Iran's Newest Robot Is an Adorable Dancing Humanoid
IEEE Spectrum
Erico Guizzo
July 12, 2017
Researchers at the University of Tehran in Iran have developed Surena Mini, a small robot with a 3D-printed body, articulated limbs, and a round head with two camera-eyes. In addition, the humanoid robot has 20 small servomotors that power its arms, legs, and neck, which enable it to walk, gesture, and dance. "The main purpose of this robot is to provide researchers and students with a reliable robotic platform for educational and research applications," says University of Tehran professor Aghil Yousefi-Koma. Surena Mini is equipped with a compact computer, cameras and infrared sensors, speakers, and an inertial measurement unit. Although its hands are not designed for grasping objects, it can push or chop small objects. Yousefi-Koma says one of the project's biggest challenges was implementing features such as face detection and voice recognition, which would enable the robot to perform with a greater level of autonomy.
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Who Needs Hard Drives? Scientists Store Film Clip in DNA
The New York Times
Gina Kolata
July 12, 2017
A video clip of a galloping horse, which was originally one of the very first motion pictures ever made, is now also the first movie ever to be encoded in the DNA of a living cell, where it can be retrieved at will and manipulated indefinitely as the host divides and grows. This breakthrough, achieved by researchers at Harvard Medical School, represents the latest example of the genome's potential as a data storage device. The Harvard team next wants to program bacteria to interact with human cells and record a "movie" of each cell's life. Physicist Richard Feynman in a 1959 lecture suggested DNA could be used for storage, which University of Southern California professor Leonard Adleman says was an inspiration for his research into DNA as a storage medium. University of Minnesota professor Andrew Odlyzko calls the Harvard research fascinating, and says it could lead to "the impossibility of controlling secrets."
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NTU Team Breaks Captcha System for Global Award
Straits Times
Yap Li Yin
July 14, 2017
Researchers at Nanyang Technological University (NTU) in Singapore achieved a perfect accuracy score in the Captcha component of the student cluster competition at the International Supercomputing Conference held in Frankfurt, Germany, last month. The competition included 11 student university teams, each of which had to develop a network that could recognize and read the letters in Captcha images. Each team was given training images to build a model with its computing cluster, after which unseen images were tested on the model. The NTU team received the Deep Learning Award for its exceptional performance in that component. The teams from Tsinghua and Beihang universities in China also attained perfect accuracy scores and received the same award. "This achievement has shown that Singapore is on track towards building strong high-performance computing competencies among our institutions of higher learning," says National Supercomputing Center Singapore professor Tan Tin Wee.
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WikiLeaks Gave Trump Edge in Campaign, Tweets Show
University of Edinburgh
July 12, 2017
Researchers at the University of Edinburgh in the U.K. have found that viral tweets during the final two months of the 2016 presidential campaign show Hillary Clinton was much more heavily criticized on social media compared to Donald Trump. The researchers used a computer analysis to study nearly 3,500 social media posts, which together were retweeted more than 25 million times. They found posts relating to WikiLeaks were the most common form of attack on social media for Clinton, who also was heavily criticized on Twitter over a U.S. Federal Bureau of Investigation probe into her use of a private email server. An examination of the top 50 most retweeted posts each day between Sept. 1 and Nov. 8, 2016, found there were three times as many posts attacking Clinton than posts in her favor, compared to posts related to Trump, which were split equally in favor of and against his campaign.
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Your Best Teammate Might Someday Be an Algorithm
Technology Review
Will Knight
July 10, 2017
Google's People + AI Research (PAIR) project aims to develop and release tools designed to help make the inner workings of artificial intelligence (AI) systems more transparent. In addition, Google is launching several research initiatives aimed at finding new ways for humans and AI systems to collaborate effectively. Google researchers Fernanda Viegas and Martin Wattenberg, who specialize in developing visualizations that make complex information more comprehensible, are leading PAIR. The project recently released two tools for visualizing the types of large datasets used to train a machine learning model to make useful predictions. The visualizations can help researchers identify outliers in training data. "The past few years have seen rapid advances in machine learning, with dramatic improvements in technical performance," the researchers say. "But we believe AI can go much further--and be more useful to all of us--if we build systems with people in mind at the start of the process."
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A New System to Estimate the Duration of a Walk in the Countryside
University of Seville
Joaquin Marquez
July 11, 2017
Researchers at the University of Seville in Spain have developed a system to estimate the time that it takes to complete a walk in the countryside. The system includes an algorithm that accounts for the length and gradient as the main variables when establishing how long a walk takes. The researchers applied their method to routes across Spain, and concluded the formula provides a better approximation of the time that will be taken by an average hiker compared to other conventional systems. They say the algorithm can be a useful tool for organizations that manage these routes, as they will be able to give walkers better estimates of the duration of the routes and help them better understand infrastructure needs. In addition, the algorithm can give an estimate for routes that have not been walked before.
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Miniaturizing the Brain of a Drone
MIT News
Jennifer Chu
July 11, 2017
Researchers at the Massachusetts Institute of Technology (MIT) have developed Navion, a new computer chip that uses a fraction of the power of larger drone computers and is specifically designed for a drone as small as a bottlecap. The researchers developed a low-power algorithm, in conjunction with smaller hardware, to create the specialized computer chip. Normally, after an algorithm is designed, it is given to a hardware expert to determine how to map the algorithm to hardware. "But we found by designing the hardware and algorithms together, we can achieve more substantial power savings," says MIT professor Vivienne Sze. The chip processes streaming images at 20 frames per second, using just below two watts of power, and automatically carries out commands to adjust a drone's orientation in space. MIT professor Sertac Karaman notes this design is the first step toward creating the smallest intelligent drone that can fly on its own.
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Testing Brain-Inspired Chips for Big Data Problems at Berkeley Lab
Inside HPC
July 10, 2017
Researchers in the Computational Research Division at Lawrence Berkeley National Laboratory say neuromorphic computing systems could help alleviate big data challenges. One group of researchers is looking at how these miniscule, low-power chips might be able to provide real-time data processing for charged particle tracking in high-energy physics experiments as well as predict movement from neural signals for brain-machine interfaces. They want to implement Kalman filters on IBM's TrueNorth chips to expand the technology to any computing problem benefiting from real-time, continuous tracking or control. Another group is examining the viability of applying convolutional neural networks on TrueNorth. The goal is to classify images and extract features from experimental observations generated at U.S. Department of Energy facilities. Based on initial results, the team currently is working to identify problems in the areas of structural biology, materials science, and cosmology that may benefit from this setup.
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U.S. Defense Department Funding $1.6 Million Algorithm Study at Texas A&M
Texas A&M Today
Richard Nira
July 10, 2017
Texas A&M University researchers are examining new, commonly used computational processes to understand how algorithms reach the conclusions they do, as part of a four-year, $1.6-million U.S. Defense Advanced Research Projects Agency (DARPA) project. Texas A&M professor Eric Ragan says in order to have confidence in an algorithm's recommendations, end users need to know why an algorithm is advising them to take a particular action. Ragan says the researchers are modeling the steps that result in an algorithm's outcome and creating visualizations of the models in an effort to make the "why" understood to end users. "Tentative plans are to test the effectiveness of the charts to show the most important information in the model," he says. The project is one of 13 DARPA-funded studies to develop artificial intelligence techniques that include explanations of algorithmic reasoning.
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MIT IoT and Wearable Project Foretells the Future of Industrial Safety
Network World
Steven Max Patterson
July 10, 2017
A multidisciplinary team from the Massachusetts Institute of Technology Design Lab led by Guillermo Bernal last month won best research paper at the PErvasive Technologies Related to Assistive Environments (PETRA 2017) conference in Greece for its work in applying Internet of Things (IoT) and wearables technology to industrial safety. Their prototype system features a jacket connected to peers and the supervisor's dashboard via a ZigBee mesh network. Bio-sensors communicate individually, and the system analyzes their data to measure stress and other vital states of the wearer. The data is selectively reported to peers through haptic sensation and to the dashboard. The jacket provides advance warning of potential harm to the wearer, and it monitors the entire work environment via bio- and environmental sensors. A carabiner pressure sensor reports if it is attached, and an altimeter detects if the worker has climbed to a hazardous height.
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Researchers Revolutionize Brain-Computer Interfaces Using Silicon Electronics
Columbia University
Holly Evarts
July 10, 2017
Columbia University researchers received a four-year, $15.8-million grant from the U.S. Defense Advanced Research Projects Agency (DARPA) to invent an implanted brain-interface device that could benefit the lives of people with neurodegenerative diseases or those who are hearing and visually impaired. The project is part of DARPA's Neural Engineering System Design (NESD) program, which itself is part of the larger BRAIN Initiative. NESD is aimed at developing an implantable neural interface that can provide better signal resolution and data-transfer bandwidth between the brain and the digital world. The implanted chips are ultra-conformable to the brain surface, very light, and flexible enough to move with the tissue. "By using the state-of-the-art in silicon nanoelectronics and applying it in unusual ways, we are hoping to have a big impact on brain-computer interfaces," says Columbia professor Ken Shepard.
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