Welcome to the January 27, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Women Primed to Fill Cybersecurity Talent Gap
Financial Times
Alice Kantor
January 25, 2021
Cybersecurity analysts are in great demand thanks to the surge in remote work due to the pandemic. A survey by the International Information System Security Certification Consortium found 3.1 million cybersecurity analysts are needed worldwide, with 22% of companies having faced a substantial shortfall of dedicated cybersecurity staff from April to June 2020. Cyberanalyst Jane Frankland said hiring more women can help narrow the talent gap, as they comprise just 25% of the sector's workforce. The U.K. government and other organizations are striving to remedy women's historic underrepresentation, but Emily Stapf at financial services group PricewaterhouseCoopers said retention is the key obstacle. Stapf said hiring and retaining women could help cybersecurity's role evolve from asset protection to a corporate value-add, because "many women have a risk management mindset, think differently about balancing tasks, and are able to sort through the noise to identify a threat."
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Designing Customized 'Brains' for Robots
MIT News
Daniel Ackerman
January 21, 2021
Researchers at the Massachusetts Institute of Technology and Harvard University have developed a system that can increase a robot's efficiency by minimizing the mismatch between the robot’s “mind” and body. Robomorphic computing generates a customized chip design based on a particular robot's parameters, such as limb layout and joint movement, and computing needs. The researchers programmed a customizable field-programmable gate array chip according to the system's suggestions, and the chip performed eight times faster than an off-the-shelf CPU and 86 times faster than an off-the-shelf GPU despite operating at a slower clock rate. Said Harvard's Brian Plancher, "Ideally we can eventually fabricate a custom motion-planning chip for every robot, allowing them to quickly compute safe and efficient motions."
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They Found Way to Limit Big Tech's Power: Using the Design of Bitcoin
The New York Times
Nathaniel Popper
January 26, 2021
Technologists, investors, and everyday Internet users are pushing to replace basic online building blocks in ways that are harder for major technology companies like Facebook and Google to dominate, increasingly looking to the design of the bitcoin cryptocurrency. Bitcoins are created and routed by a decentralized computer network via underlying blockchain technology. Companies are finding ways to use blockchains, and technology inspired by them, to generate social media networks, store online content, and host websites in a decentralized manner, which can thwart governments or companies from banning or deleting accounts. In one example, the new Brave browser recently announced it would start integrating the blockchain-based system IPFS into its software, to boost the reliability of Web content in the event big service providers went out of operation or attempted to ban sites.
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Scientists Use Novel Ink to 3D-Print 'Bone' With Living Cells
University of New South Wales (Australia)
Lachlan Gilbert
January 25, 2021
A technology developed by researchers at Australia's University of New South Wales (UNSW) Sydney enables three-dimensional (3D) printers to print bone-like structures complete with living cells. The researchers developed an ink comprised of calcium phosphate, and their new technique, called ceramic omnidirectional bioprinting in cell-suspensions (COBICS), allows 3D printing of bone-like structures that harden in minutes when placed in water. This marks the first time that such structures were created at room temperature without harsh chemicals or radiation and including living cells. UNSW's Kristopher Kilian said, "We can go directly into the bone where there are cells, blood vessels, and fat, and print a bone-like structure that already contains living cells, right in that area. There are currently no technologies that can do that directly."
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Cardiovascular Diseases: Computer Model Improves Therapy
Graz University of Technology (Austria)
Christoph Pelzl
January 22, 2021
Researchers at Austria's University of Graz and the Graz University of Technology (TU Graz) have generated digital twins of human hearts, which doctors can use to pre-model optimal therapies and improve the likelihood of successful treatment for cardiovascular diseases. Imaging algorithms construct a digital twin from diagnostic data, which provides information to help understand the individual clinical situation and consider various therapeutic scenarios. TU Graz's Thomas Pock said computerized heartbeat simulation requires calculating millions of factors, and demands "complex mathematical procedures, special algorithms, and special hardware that can perform billions of computing actions per second." The new technique can routinely produce anatomically accurate digital twins of patient hearts in clinical environments.
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Chess Engine Sacrifices Mastery to Mimic Human Play
Cornell Chronicle
Melanie Lefkowitz
January 25, 2021
A team of researchers from Cornell University, Canada's University of Toronto, and Microsoft Research have developed an artificial intelligence chess engine that is trained to play like, rather than beat, humans. The Maia chess engine was taught to mimic human behavior through training on individual human chess moves, instead of the larger problem of winning the game. The researchers found Maia matched human moves within each skill level over 50% of the time, an accuracy rate higher than those of the popular chess engines Stockfish and Leela. Cornell's Jon Kleinberg said, "Our model didn't train itself on the best move; it trained itself on what a human would do. But we had to be very careful—you have to make sure it doesn't search the tree of possible moves too thoroughly, because that would make it too good. It has to just be laser-focused on predicting what a person would do next."
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Merging Technologies with Color to Avoid Design Failures
Penn State College of Engineering
Miranda Buckheit
January 21, 2021
Pennsylvania State University (Penn State) researchers analyzed machine learning (ML) and image colorization algorithms to avoid design failures. Penn State's Pranav Milind Khanolkar reviewed the use of the ABAQUS additive-manufacturing simulation software, which can pose difficulties because its speed and performance level rely on a computer's hardware processing power. The team deployed ML algorithms to lower the exclusive use of computationally demanding finite element analysis, and accelerate simulations. It then applied image colorization algorithms to material microstructure data, and repurposed programs typically used to add color to monochrome photos. Khanolkar said, "Using intelligent technology to help people and empower their creativity and empathy during the design process is important. These algorithms need lots of computational power and using artificial intelligence ... allows designers to be more creative without impacting production cost."
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Less Is More: IBM Achieves Quantum Computing Simulation for Materials with Fewer Qubits
ZDNet
Daphne Leprince-Ringuet
January 21, 2021
A quantum computing simulation for new materials realized by IBM researchers utilizes fewer quantum bits (qubits), reducing computational cost while increasing model precision. IBM's quantum computers, like most quantum systems, operate with less than 100 qubits, which is not enough for modeling molecules sufficiently complex for more advanced material properties. The IBM team produced a “transcorrelated” Hamiltonian mathematical function representing particles' orbitals to contain more data about electron behavior in a particular molecule; this boosted simulation accuracy without requiring additional qubits. The researchers said the development of better modelling and simulations “will ultimately result in the prediction of new materials with specific properties of interest."
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Researchers Propose Porcupine, a Compiler for Homomorphic Encryption
VentureBeat
Kyle Wiggers
January 22, 2021
A synthesizing compiler for homomorphic encryption (HE) created by researchers at Facebook and New York and Stanford universities can translate a plain-text, unencrypted codebase into encrypted code on the fly. The compiler, Porcupine, reportedly can accelerate HE up to 51% over heuristic-driven, hand-optimized code. Porcupine can convert a reference of a plain-text code into HE code that performs the same computation, by internally modeling instruction noise, latency, behavior, and HE program semantics with the Quill component. Quill lets Porcupine reason about and seek kernels that are verifiably correct while minimizing latency and noise accrual, yielding a suite that automates and optimizes the mapping and scheduling of plain text to HE code. According to the researchers, "Porcupine abstracts away the details of constructing correct HE computation so that application designers can concentrate on other design considerations."
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Lasers, VR to Revolutionize Watch-Crystal Engraving
EPFL (Switzerland)
January 25, 2021
Engineers at the Swiss Federal Institute of Technology, Lausanne (EPFL) and Swiss luxury watchmaker Vacheron Constantin have engraved watch crystals using a combination of lasers and virtual reality (VR). Developed over several years, the technique incorporates VR to recreate tactile feedback that is otherwise lost in the switch to laser engraving, according to EPFL's Yves Bellouard. Specialists at EPFL spin-off Force Dimension, a surgical robotics technology developer, designed a digital pen attached to a robotic arm that uses haptics to imbue a sense of touch to users as they engrave materials virtually. Vacheron Constantin's Paul Bertusi said. "Being able to structure watch crystals in 3D (three dimensions), work anywhere in a piece of crystal, and create genuine 3D sculptures within a crystal—all that opens up extremely interesting possibilities."
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When a Story is Breaking, AI Can Help Consumers Identify Fake News
Rensselaer Polytechnic Institute
Jeanne Hedden Gallagher
January 21, 2021
Rensselaer Polytechnic Institute (RPI) researchers determined that artificial intelligence (AI) can help assess news stories accurately, but only when a story is first emerging. Overall, the RPI team found AI-driven interventions are ineffective when used to flag issues with stories on frequently covered subjects about which people have established convictions. Yet tailored AI-generated advice can help readers make better judgments on the legitimacy of news articles when the topic is too fresh for opinions to emerge. This intervention is most effective when it provides reasoning in line with a person's natural thought process, like an assessment of the accuracy of facts provided or the source's reliability. RPI's Dorit Nero said, "If we can get to people early on when the story breaks and use specific rationales to explain why the AI is making the judgment, they're more likely to accept the advice."
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Battle of the Robots Still Favors Japan, Europe—For Now
The Wall Street Journal
Jacky Wong
January 20, 2021
China continues to be the biggest market for industrial robots, even though the market’s growth had been slowing prior to the pandemic, due to the U.S.-China trade war. The International Federation of Robotics reported 140,500 new installations of industrial robots in China in 2019, down 9% from the prior year but nearly three times the number of installations seen in second-place Japan. As China has gotten the Covid-19 pandemic under control, demand for automation equipment picked up, and Credit Suisse estimates that China's industrial-robotics market grew 9.5% last year. Citi reported that nearly three-quarters of China's industrial-robotics market is controlled by foreign firms like Japan's Fanuc and Europe's ABB, but some Chinese automation-equipment companies grew their market shares last year due to Covid-related supply-chain disruptions among their foreign rivals.
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Data Science, Computational Mathematics Unite to Advance Predictive Methods in Engineering
University of Cambridge (U.K.)
January 21, 2021
A Finite Element Method (FEM) redesigned by engineers at the U.K.'s University of Cambridge and The Alan Turing Institute, along with colleagues at the University of Western Australia, provides a platform for the realization of digital twins in the prediction of physical models. Cambridge's Mark Girolami said, "By accepting that our mathematical descriptions of complex systems can be wrong and not capture all aspects of the system, we were able to define a statistical description of the FEM that provided a very natural and entirely novel way to blend data and mathematical models in a really powerful way." Girolami added that this advance could pair statistical techniques with FEMs to ultimately revolutionize digital twins.
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