Welcome to the July 24, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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2020 Class of SIGHPC Computational and Data Science Fellows Announced
HPCwire
July 23, 2020
ACM's Special Interest Group on High Performance Computing (SIGHPC) has announced this year's Computational and Data Science Fellowships, which aim to boost the diversity of students pursuing graduate degrees in those fields through an annual $15,000 grant. Nominees covered disciplines ranging from biochemistry and behavioral science to engineering and geosciences, and represented large, mid-sized, and small institutions around the world. Nominees were ranked according to their potential for excellence in data science and/or computational science, and the degree to which they will serve as leaders and role models to increase diversity. Of this year's 12 fellows, nine identify as female, and five were identified as underrepresented minorities in their countries of study. SIGHPC chair John West said, "A key to ensuring a robust workforce for our field is to focus on diversifying the expertise, backgrounds, and perspectives of students studying the computational sciences."
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U.S. Hatches Plan to Build Quantum Internet That Might Be Unhackable
The Washington Post
Jeanne Whalen
July 23, 2020
U.S. officials and scientists yesterday unveiled a plan to construct a potentially hackproof quantum Internet to operate parallel to the world's existing networks. The Department of Energy (DoE) and its national laboratories will form the project's main support pillar, and DoE official Paul Dabbar suggested it could be funded using some of the $500 million to $700 million in annual federal quantum information technology investments. A quantum Internet relies on entangled photons to share information over long distances without physical links; the race to create one is a global competition. Researchers said attempts to observe or disrupt photons or quantum bits in a quantum Internet would automatically change their state and destroy the transmitted information. A quantum Internet also could interconnect various quantum systems and boost their computing power.
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3D-Printed Artery Can Monitor Blockages From the Inside
UW-Madison News
Jason Daley
July 22, 2020
University of Wisconsin-Madison (UW-Madison) engineers are developing a three-dimensionally (3D)-printed artery that lets doctors and patients remotely monitor blockages from within. The tubular artery is fabricated from a flexible ferroelectric composite, and printed by off-the-shelf equipment that extrudes the material through an electric field near the nozzle to polarize the ceramic particles and render the structure piezoelectric. UW-Madison's Xudong Wang said the implantable vessel can generate electric pulses in response to pressure fluctuations, reading internal blood pressure without additional power sources; the 3D geometry allows the electric pulse profile to detect irregular motion caused by blockages. Tests with an artificial heart system proved the self-powered material could correctly detect internal changes in force and pressure within the artery.
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Popular Chinese-Made Drone Found to Have Security Weakness
The New York Times
Paul Mozur; Julian E. Barnes; Aaron Krolik
July 23, 2020; et al.
Cybersecurity researchers found a vulnerability in an application that pilots the world's most popular consumer aerial drones, made by China-based Da Jiang Innovations (DJI). Investigators from the France-based Synacktiv and U.S.-based GRIMM security firms said the app records personal information from phones that could be exploited by China's government; DJI also can update the app and pass changes to customers before Google can review them. DJI claimed its app forces updates on users to stop hobbyists from attempting to hack the app to bypass government restrictions on geofencing and altitude. Much of the information the app collects dovetails with Chinese government surveillance practices, which require phones and drones to be connected to a user's identity. U.S. Cybersecurity and Infrastructure Security Agency director Christopher Krebs said, "This ... is a good reminder that organizations need to pay attention to the risks associated with the various technologies they're using for operations."
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Blueprint for the Perfect Coronavirus App
ETH Zurich (Switzerland)
Felix Wursten
July 20, 2020
Researchers at the Swiss Federal Institute of Technology in Zurich (ETH Zurich) have outlined the ethical and legal challenges of developing and implementing digital tools for managing the Covid-19 pandemic. The authors highlighted contact-tracing applications, programs for assessing an infection's presence based on symptoms, apps to check compliance of quarantine regulations, and flow models like those Google uses for mobility reports. ETH Zurich's Effy Vayena said rigorous scientific validation must ensure digital tools work as intended, and confirm their efficacy and reliability. Ethical issues include ensuring data collected by apps is not used for any other purpose without users' prior knowledge, and deploying tools for limited periods to deter their misuse for population surveillance. Vayena said, "The basic principles—respecting autonomy and privacy, promoting healthcare and solidarity, and preventing new infections and malicious behavior—are the same everywhere."
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New York Bans Facial Recognition in Schools Statewide
VentureBeat
Kyle Wiggers
July 22, 2020
The New York State legislature Wednesday passed a moratorium on the use of facial recognition and other biometric identification methods in schools statewide until 2022, in response to a planned rollout by the Lockport City School District. Although advocates claim the Aegis system from Canada-based SN Technologies keeps students safe by enforcing watchlists and flagging people as dangerous or otherwise unwanted, critics say it could be used to spy on students, or to compile a database of sensitive facial information that the district might have difficulty securing. The bill, not yet signed into law by Governor Andrew Cuomo, would require the New York State Education Department to probe the issue of biometric identification in schools before crafting regulations. Stefanie Coyle with the New York Civil Liberties Union supports the moratorium, noting that facial recognition is "notoriously inaccurate" in identifying women and people of color. ACM and the American Civil Liberties Union also are urging moratoriums on biometric identification.
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Researchers Offer Solution for One of Synthetic Biology's Biggest Problems
Penn State News
Jamie Oberdick
July 21, 2020
Researchers at Pennsylvania State University (Penn State) and the University of Washington developed an algorithm to help prevent the malfunction of engineered genetic systems, a major challenge in synthetic biology. The problem stems from reuse of genetic components in multiple locations or components with similar DNA sequences, often inducing spontaneous DNA breakage that nullifies the newly added capabilities. The researchers used the Non-Repetitive Parts Calculator algorithm to generate thousands of highly non-repetitive genetic parts with desired functions. The team engineered, constructed, and characterized 4,350 non-repetitive bacterial promoters and 1,722 highly non-repetitive yeast promoters. Penn State's Howard Salis said the algorithm will help eliminate self-deletion of added DNA in engineered organisms, and prevent the loss of millions of dollars in research and development.
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Top Programming Languages 2020
IEEE Spectrum
Stephen Cass
July 22, 2020
Python's dominance as the most popular programming language is holding steady in 2020, according to IEEE Spectrum's latest rankings of top languages. These rankings are based on a combination of metrics from online sources considered solid proxies for the popularity of 55 programming languages. Java and C maintained their respective second- and third-place listings in the new ranking, while Arduino climbed from 11th place in the last ranking to seventh place. One could credit Python's high ranking to metrics inflated by its growing use as a language for instruction, yet Python often is used professionally and in high-profile domains like machine learning, thanks to its massive collection of high-quality, specialized archives. The Covid-19 pandemic appears to have had an impact, with the Twitter metric listing Cobol in seventh place, likely because demand for the language was high in April amid calls to upgrade unemployment benefit systems crashing as a result of lockdowns.
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Intelligent Sensing Abilities for Robots to Carry Out Complex Tasks
National University of Singapore
July 15, 2020
Researchers at the National University of Singapore (NUS) have developed a sensory integrated artificial brain system that mimics biological neural networks in order to make robots smarter and more intuitive. The system features an artificial skin sensor that can identify an object's shape, texture, and hardness 10 times faster than the blink of an eye. Intel's Loihi neuromorphic research chip processes sensory data from the artificial skin. The researchers used a robotic hand equipped with the artificial skin to read Braille; tactile data was passed to the Loihi chip, which was more than 92% accurate in classifying the Braille letters. By combining both vision and touch data in a spiking neural network, the robot was able to classify objects and detect object slippage. Said NUS' Harold Soh, "[A] neuromorphic system is a promising piece of the puzzle for combining multiple sensors to improve robot perception."
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Self-Driving Industry Takes to the Highway After Robotaxi Failure
Financial Times
Patrick McGee
July 19, 2020
The autonomous vehicle industry is refocusing on more-profitable opportunities after efforts to commercialize robotaxis failed to live up to the hype. Harvard University's Ashley Nunes said, "Bringing [self-driving] tech to market will require fundamentally rethinking the concept by scaling back where and how the tech can be deployed and the types of returns investors can expect." Practical services garnering interest include grocery delivery and automated warehouse robots. Autonomous vehicle startups see potential in the U.S. trucking industry; one concept involves building transfer hubs near highways to where drivers would deliver freight to a self-driving truck that would carry it to the next hub for hand-off back to humans. Passenger-only cars are another area of interest for highway-only autonomy, as LiDAR companies team with automakers to build more affordable units at scale.
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Enabling Fairer Data Clusters for Machine Learning
The Michigan Engineer News Center
July 17, 2020
Computer science and engineering investigators at the University of Michigan (UMich) and Stony Brook University have created a method for fairly scheduling high volumes of machine learning tasks in heterogeneous data clusters that use of multiple types of computing hardware (like central processing units, graphics processing units, and specialized accelerators). The AlloX tool addresses the challenge of different hardware optimally handling different tasks. The researchers found AlloX reduced average job completion time by up to 95% when the system load was high, while supporting fairness and preventing job starvation. Said UMich’s Mosharaf Chowdhury, “We show that you can be fair and your average will still remain close to the optimized average.”
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Researchers Developing Tools to Calculate AI's Carbon Footprint
The Wall Street Journal
Sara Castellanos
July 17, 2020
Researchers in Canada and the U.S. are creating tools to calculate the carbon footprint of artificial intelligence (AI) models in order to help developers understand their environmental impact. The goal is to encourage scientists to ameliorate such effects by training algorithms on servers that run on hydroelectricity or solar power, using less training data and pre-trained models. Sasha Luccioni at Canada's Mila-Quebec AI Institute is co-developing a tool expected to be released in September that produces an estimate of carbon dioxide emissions attributable to the training of an AI model, based on the energy grid the user is connected to, the processors employed, and the model's runtime. Meanwhile, a U.S.-Canadian team developed a carbon-footprint calculator for machine learning experiments, which they released for free on GitHub in February. Said Stanford University's Peter Henderson, “Our main goal was basically to raise awareness.”
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