Welcome to the February 18, 2022, edition of ACM TechNews, providing timely information for IT professionals three times a week.
Please note: In observance of the U.S. Presidents' Day holiday, TechNews will not be published on Monday, Feb. 21. Publication will resume Wednesday, Feb. 23. ACM TechNews mobile apps are available for Android phones and tablets (click here) and for iPhones (click here) and iPads (click here).
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Tech Companies Face a Fresh Crisis: Hiring
The New York Times Susan Dominus February 16, 2022
Recruiters for technology companies are finding it difficult to connect with potential candidates despite the high demand for tech workers. Research indicates unemployment rates for tech workers are about 1.7%, and 0.2% for those with experience in cybersecurity, versus 4% for the general economy. As a result, recruiters often must inform tech executives that candidates have multiple, and sometimes better, offers. They also have to tell executives that they may have to hire someone with slightly less experience. Ryan Sutton of staffing firm Robert Half said to clients looking for software designers, "If you are not going to offer remote work, if you're not going to offer at least hybrid, we can't help you."
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African Software Developers Use AI to Fight Inequality
Reuters Kim Harrisberg February 16, 2022
Developers like South African computer scientist Raesetje Sefala hope to combat inequality across Africa by harnessing artificial intelligence (AI). Sefala says local knowledge is critical for designing workable AI-driven solutions; she has created algorithms that flag poverty hotspots. Meanwhile, Togo's government partnered with the Innovations for Poverty Action think tank and the University of California, Berkeley to build the Novissi mobile payment platform to help distribute cash to vulnerable informal workers during the COVID-19 pandemic. That group mapped poverty areas in Togo via satellite imagery, then used algorithms supported by the GiveDirectly nonprofit to identify potential recipients of that funding.
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Adaptive LED Headlights Get NHTSA Approval in the U.S.
motor1.com Christopher Smith February 15, 2022
The U.S. National Highway Transportation Safety Administration issued a new rule permitting the use of adaptive light-emitting diode (LED) headlights on U.S. roads. The $1-billion infrastructure bill passed in November contained a measure allowing the rule against use of such headlights in the U.S. to be modified. The housings of adaptive headlights contain computer-controlled LEDs that can be aimed in specific locations; they can illuminate the road ahead of the driver similar to the way high beams can, while also focusing the light away from oncoming traffic. Luxury automakers like Mercedes-Benz and Audi have been using adaptive headlights in their vehicles for years; while the legal hurdles have been cleared, their U.S. deployment will likely not happen quickly.
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DNA Computer Assesses Water Quality
Northwestern University McCormick School of Engineering Amanda Morris February 17, 2022
Northwestern University McCormick School of Engineering scientists have developed an inexpensive handheld device that can confirm water's potability in minutes, by using DNA-based circuits. The researchers assembled cell-free molecules into an analog-to-digital converter, which causes test tubes to glow green when contaminants are present in the sample. The system upgrades the ROSALIND (RNA output sensors activated by ligand induction) contaminant detector with a genetic network. Northwestern's Julius B. Lucks said, "The bio-sensor detects contamination, but then the output of the bio-sensor feeds into the genetic network, or circuit, which works like a brain to perform logic."
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Algorithm Could Shorten Quality Testing, Research in Many Industries by Months
Sandia National Laboratories February 15, 2022
Researchers at Sandia National Laboratories and Ohio State University have developed a machine-learning algorithm that could make industrial testing of bulk materials faster and less expensive. For the algorithm called MAD 3, said Sandia's Montes de Oca Zapiain, "We've trained the model to understand the relationship between crystallographic texture and anisotropic mechanical response. You need an electron microscope to get the texture of a metal, but then you can drop that information into the algorithm, and it predicts the data you need for the simulation software without performing any mechanical tests." The algorithm was trained on the results of 54,000 simulated materials tests using a feed-forward neural network. Said Sandia's Hojun Lim, "The developed algorithm is about 1,000 times faster compared to high-fidelity simulations."
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Illinois Musicians, Chemists Use Sound to Better Understand Science
University of Illinois News Bureau Jodi Heckel February 17, 2022
Musicians and chemists at the University of Illinois Urbana-Champaign (UIUC) are using sound to investigate and visualize biochemical processes in order to understand them better. UIUC’s Carla Scaletti produced an animated visualization coupled with sound to illustrate protein folding, based on massive volumes of data. Scaletti and UIUC’s Stephen Andrew Taylor applied audio mapping to connect aspects of proteins to sound parameters like pitch, timbre, loudness, and pan position. “In digital audio, everything is a stream of numbers, so actually it’s quite natural to take a stream of numbers and listen to it as if it’s a digital recording,” said Scaletti, adding that unseen aspects of some compounds can be revealed through sound.
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Fake Faces Created by AI Look More Trustworthy than Real People
New Scientist Christa Lesté-Lasserre February 14, 2022
Researchers at the U.K.'s Lancaster University and the University of California, Berkeley found that people have a hard time distinguishing images of human faces created by artificial intelligence from images of real faces. The researchers asked a group of 315 people to distinguish a selection of 400 fake photos from 400 photos of real people; they were accurate less than half (48.2%) of the time (a second group trained to recognize computer-generated faces did slightly better, with an accuracy rate of 59%). The researchers found that white faces were hardest for participants to distinguish, possibly due to the software being trained on disproportionally more white faces.
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Predicting Complex Dynamics From Data
ETH Zurich (Switzerland) Oliver Morsch February 15, 2022
An algorithm created by researchers at the Swiss Federal Institute of Technology, Zurich (ETH Zurich) and Germany's University of Bremen allows them to predict complex dynamics from experimental data. "Our new approach relies on the realization that one doesn't need to reproduce all the details of the dynamics, but only its key structures," said ETH Zurich's Mattia Cenedese. The algorithm applies a holistic approach to dynamical systems, which can reduce the amount of time for calculations from several hours or days to a few minutes. The researchers fed the results of a water-tank experiment to the algorithm, which generated a nonlinear mathematical model that accurately captured the observed sloshing motion of water. The model also accurately forecast the resulting water motion for different frequencies of shaking, despite having never observed such an experiment before.
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Cancer Computer Models Identify Drug Combinations to Treat COVID-19
University College London (U.K.) February 15, 2022
Researchers at the U.K.'s University College London (UCL) have identified new drug combinations that could be used to treat different stages of severe COVID-19 infection. The researchers accomplished this by adapting computer models previously developed by UCL researchers to simulate the biochemical and metabolic pathways of cells and their impact on cancer-causing mutations. The researchers used the models to study the effect of 9,870 pairs of compounds acting on 140 potential cellular targets, which yielded new combinations of therapeutics that could be beneficial to patients in the early or late stages of COVID-19. Said UCL's Jasmin Fisher, "Our model is both a highly efficient way of prioritizing drugs for evaluation as treatments for COVID-19 and could also help ensure that COVID-19 patients get the right drug at the right time."
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Top Half of a Robot Giraffe
IEEE Spectrum Evan Ackerman February 16, 2022
Attempts to mimic a giraffe's neck by researchers at Japan's Tokyo Institute of Technology have yielded a half-scale musculoskeletal robot. The Giraffe Neck Robot #1 combines a three-dimensionally-printed skeletal mechanism, a gravity compensation mechanism that emulates the nuchal ligament, a redundant muscle driving system, and a ligament-imitative joint that uses rubber disks. The robot giraffe neck features similarly arranged vertebrae and tendons, and thin McKibben pneumatic artificial muscles that deliver contractions like real muscles.
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What's Inside a Black Hole? Physicist Probes Holographic Duality with Quantum Computing to Find Out
SciTechDaily February 14, 2022
University of Michigan physicist Enrico Rinaldi and colleagues are investigating holographic duality—the concept of mathematical equivalence between the theories of gravity and particles—through the use of quantum computing and machine learning. The researchers described the gravity of a black hole by solving quantum matrix models using two simulation techniques. They characterized the mathematical description of the quantum state in their matrix model, or the quantum wave function. They then applied a neural network to find the wave function with the lowest possible energy, or ground state, through iterative optimization. "Because these matrices are one possible representation for a special type of black hole, if we know how the matrices are arranged and what their properties are, we can know, for example, what a black hole looks like on the inside," said Rinaldi.
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Google's 'CEO' Image Search Gender Bias Hasn't Really Been Fixed
University of Washington News Sarah McQuate February 16, 2022
University of Washington (UW) researchers have disproved Google's claims it corrected gender biases for certain job terms in its image search that was uncovered in 2015 by another UW team. The researchers showed Google has only partly fixed the problem, demonstrating that adding another search term to the profession—"CEO + United States," for example—returned fewer photos of cis-female-presenting people than cis-male. This bias was shown to still exist across four major global search engines, including Google. "We wanted to be able to show that this is a problem that can be systematically fixed for all search terms, instead of something that has to be fixed with this kind of 'whack-a-mole' approach, one problem at a time," said UW's Chirag Shah.
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Research Advances Technology of AI Assistance for Anesthesiologists
MIT News David Orenstein February 14, 2022
Massachusetts Institute of Technology (MIT) and Massachusetts General Hospital researchers trained a machine learning algorithm to continuously automate the administration of propofol during surgery to optimize dosage and keep patients unconscious during general anesthesia. The researchers equipped the algorithm with two neural networks: an "actor" that determined dosages in real time, and a "critic" that helped the actor maximize "rewards" directed by the programmer. The most effective reward framework was a "dose penalty" setup, in which the critic questioned every dose the actor administered, continuously scolding it to keep dosing to a necessary minimum to maintain unconsciousness. The algorithm outperformed more conventional software in physiology-based patient models. MIT's Emery N. Brown said, "Algorithms such as this one allow anesthesiologists to maintain more careful, near-continuous vigilance over the patient during general anesthesia."
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