Welcome to the January 7, 2022 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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The Battle to Prevent Another January 6 Features New Weapon: The Algorithm
The Washington Post
Steven Zeitchik
January 6, 2022
Data scientists specializing in unrest prediction are applying machine learning (ML) to the causes of political violence to predict the likelihood of another January 6-like insurrection in the U.S. The University of Central Florida's CoupCast algorithm, for example, forecasts the probability of coups and electoral violence in dozens of countries every month. Following January 6, 2021, researchers reprogrammed CoupCast's model to account for factors it had previously downplayed, like the role of a leader stoking mob violence, while underplaying other factors, like long-term democratic history. Meanwhile, the nonprofit Armed Conflict Location & Event Data Project combines ML and software-equipped humans to track and predict crises worldwide.
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Body-Monitoring Tech Trend Comes with Concerns
France24
January 6, 2022
Body-monitoring technology promoted at this year's Consumer Electronics Show raises concerns about such wearables eroding the boundary between well-being and obsession. Amaury Kosman at French startup Circular said the company's Circular Ring provides wearers with a daily "energy score" based on activity intensity compiled from heart rate, body temperature, and other sensor-collected data. The ring also tracks sleeping habits, awakes users via vibrations, and syncs with a mobile application to make lifestyle recommendations. German political scientist Nils-Eyk Zimmermann warned such tools could generate a "digital self" that is out of step with reality, adding that society must ascertain whether they are beneficial or "give rise to new dependencies."
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Predicting the Future of COVID
Boston College
January 6, 2022
A new analytical tool developed by a research team led by biologists at Boston College (BC) uses quantum mechanical modeling to predict future mutations of SARS-CoV-2. BC's Babak Momeni said, "We computationally predict what mutations allow better binding to host receptors and better evasion of antibodies." The goal is to prepare for future COVID variants of concern. Said Momeni, "We use a fully quantum mechanical model to theoretically assess how different mutations in the spike [protein of the coronavirus] can contribute to its increased, or decreased, binding strength to human ACE2." The study also found that factors other than binding may be involved in determining how a variant evolves.
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A License to Print Houses
Financial Times
Louis Wustemann
December 30, 2021
As three-dimensionally (3D)-printed homes start to catch on, Logan Architecture founder Andrew Logan predicts, "20 years from now, you will be able to buy a piece of land and print your own home through an app on your phone." Several Logan-designed 3D-printed housing developments were completed in Austin, TX, in September, using software-guided robots to pipe cement walls into additive layers. Logan said 3D printing can accommodate curved walls and corners, although wall height is limited to slightly over 8 feet. The use of 3D printing could find acceptance in the mid-market housebuilding sector because of its cost advantages over human construction. For example, developer SQ4D this summer printed a three-bedroom, ranch-style house in Riverhead, NY, for $20,000, versus a $150,000 price tag for building the same house using conventional methods.
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Making AI-Generated Voices More Expressive
UC San Diego Jacobs School of Engineering
January 4, 2022
More expressive artificial intelligence-generated voices can be produced with minimal training through a method developed by computer scientists and electrical engineers at the University of California, San Diego. The researchers flagged pitch and rhythm of speech in training samples to substitute for emotion, so the voice cloning system could generate expressive speech for subjects outside its training set. "Our proposed model can make a new voice express, emote, sing, or copy the style of a given reference speech," according to the researchers. They said their new method can learn speech from text, reassemble speech samples from target speakers, and impose pitch and rhythm from a different expressive speaker onto cloned speech for the target speaker.
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Navigational Apps for the Blind Could Have Broader Appeal
The New York Times
Amanda Morris
January 4, 2022
New apps designed specifically for blind and low-vision people could also have mainstream appeal. Leveraging improvements in mapping technology and smartphone cameras, these apps can provide indoor navigation, detailed descriptions of the surrounding environment, and more warnings about obstacles. For example, MapInHood, released only in Toronto so far, offers information about sidewalk traffic, construction hazards, accessible curb cuts, and locations of benches, among other things. It also can help users avoid stairs or steep slopes, which would benefit disabled individuals as well as those carrying suitcases or pushing strollers. Meanwhile, GoodMaps is creating indoor navigational tools for airports, train stations, office buildings, malls, and hospitals. Said GoodMaps' José Gaztambide, "You as a sighted person are going to be able to enter more and more buildings and find your way around more quickly than ever before because of the work we're doing of enabling accessible navigation."
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Theoretical Breakthrough Could Boost Data Storage
MIT Computer Science and Artificial Intelligence Laboratory
Steve Nadis
January 3, 2022
Researchers at the Massachusetts Institute of Technology (MIT), Stony Brook University, and Google discovered that linear-probing hash tables can operate at high storage capacity without losing speed in applications where the number of insertions and deletions remain about the same and the amount of added data is similar to that of removed data. These findings could pave the way for more efficient data storage and retrieval in computers. The researchers also developed a "graveyard hashing" technique that, contrary to the traditional approach, artificially increases the number of tombstones placed in an array until they occupy approximately 50% of the free spots, reserving spaces for future insertions.
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Top Programming Languages: Coding Favorite Tops List Again
ZDNet
Liam Tung
January 6, 2022
Python has topped software testing outfit Tiobe's programming language list for the second year in a row as it was awarded the title of programming language of the year. The Tiobe ranking is based on the words developers use to search for a language, segmented by each language’s share of searches. Python owes its popularity to its use in machine learning and data science, and to the extensive software libraries in the Python Package index. The language runs well on high-end hardware and offers opportunities for development on cloud platforms such as Azure. "Python has it all to become the de facto standard programming language for many domains," says Tiobe’s Paul Jensen. "There are no signs that Python's triumphal march will stop soon."
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Making Quantum Computers Even More Powerful
Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Valérie Geneux
January 6, 2022
Engineers at the Swiss Federal Institute of Technology, Lausanne (EPFL) partnered with U.K. researchers to devise a technique for reading multiple quantum bits (qubits) simultaneously, in a step toward more powerful quantum computers. EPFL's Andrea Ruffino formulated a process for concurrently reading nine qubits, which could be scaled up. Ruffino developed a method for packing quantum dots into a transistor to mimic qubits, in order to undertake experiments under conditions similar to those in a quantum system. EPFL's Edoardo Charbon described Ruffino's technique as "a real breakthrough that could lead to systems of large qubit matrices integrated with the necessary electronics."
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Innovative X-ray Imaging Shows COVID-19 Can Cause Vascular Damage to the Heart
University of Göttingen (Germany)
December 21, 2021
Researchers at Germany's University of Göttingen and Hannover Medical School (MHH) found that COVID-19 can cause vascular damage to the heart. The researchers examined heart muscle tissue from people who died from COVID-19 using synchrotron radiation, a type of bright X-ray radiation, viewing the images in three dimensions. The researchers employed machine learning to observe changes in the heart at the capillary level, finding that severe COVID-19 disease caused the formation and splitting of new vessels. The researchers broke the tissue architecture down to its local symmetrical features and made comparisons. Said Göttingen's Tim Salditt and MHH's Danny Jonigk, "The parameters obtained from this then showed a completely different quality compared to healthy tissue, or even to diseases such as severe influenza or common myocarditis."
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University Loses 77TB of Research Data Due to Backup Error
BleepingComputer
Bill Toulas
December 30, 2021
Japan's Kyoto University in December lost approximately 77TB of research data due to an error in the backup system of its Hewlett-Packard supercomputer. The loss amounted to 34 million files from 14 research groups, which were unable to be restored. The type of work lost has not been disclosed. The university has halted its backup system while improvements are implemented and plans to reintroduce it in January.
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Solving the 'Big Problems' via Algorithms Enhanced by 2D Materials
Penn State News
Jamie Oberdick
January 5, 2022
Pennsylvania State University (Penn State) researchers have developed a method of solving combinatorial optimization problems using two-dimensional (2D) materials. The researchers utilized a simulated annealing algorithm to determine the ground state of an Ising spin glass system. Penn State's Amritanand Sebastian said the process involves conducting in-hardware computational operations, with the hardware deployed via 2D material-based transistors that also store data. "We make use of this in-memory computation capability in order to perform simulated annealing in an efficient manner," he explained. According to Sebastian, the method saves energy through ultra-low-power operation, allows efficient computation of the spin system's energy, and does not require the hardware to scale with the size of the problem.
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Light-Matter Interactions Simulated on World's Fastest Supercomputer
University of Tsukuba (Japan)
January 6, 2022
A research team led by Japan's University of Tsukuba simulated light-matter interactions at the atomic scale using nearly 28,000 nodes of the world's fastest supercomputer. At Japan’s RIKEN Center for Computational Science, the researchers used their SALMON (Scalable Ab initio Light-Matter simulator for Optics and Nanoscience) software, optimized to maximize performance on the Fugaku supercomputer, and tested the code by modeling light-matter interactions in a thin film of amorphous silicon dioxide. Said Tsukuba's Kazuhiro Yabana, "We found that our code is extremely efficient, achieving the goal of one second per time step of the calculation that is needed for practical applications. The performance is close to its maximum possible value, set by the bandwidth of the computer memory, and the code has the desirable property of excellent weak scalability."
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