Welcome to the July 13, 2022, edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Major American Companies to Schools: Expand Access to Computer Science
Education Week
Alyson Klein
July 12, 2022


A July 12 letter to governors and top education officials in all 50 states, signed by over 500 businesses, nonprofits, and education organizations, calls for every K-12 student to be given access to computer science education. Amazon, Microsoft, and Alphabet were among the signatories, along with companies like American Express, Nike, Starbucks, UPS, and Walgreens. Code.org reports that only about a dozen of the 27 states with policies granting access to high school students aim to give all K-12 students access. Code.org's Hadi Partovi said it is important that big companies not thought of as tech companies support the effort. Said Partovi, "It helps people realize that this is about every industry, that every company is becoming a technology company and every company is suffering with the lack of preparation that our schools are giving to our students."

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Criminal Justice Algorithm Predicts Risk of Biased Sentencing
Government Technology
Jule Pattison-Gordon
July 12, 2022


Members of the American Civil Liberties Union, Carnegie Mellon University, the Idaho Justice Project, and the University of Pennsylvania developed a criminal justice algorithm to predict the probability of defendants receiving biased sentences in court. The algorithm factors in seemingly immaterial variables like the judge's and defendant's gender and race, along with case details like mandatory minimum sentencing requirements and the nature of the offense, to forecast how likely the judge is to issue an unusually long sentence (longer than those issued in 90% of the other cases with "identical legally relevant factors"). The team of developers suggest the algorithm could help potentially wronged defendants argue for reducing disproportionately harsh sentences.

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Researchers Tackle Longstanding 'Data Heterogeneity' Problem for Federated Learning
NC State University News
Matt Shipman
July 11, 2022


A federated learning approach developed by North Carolina State University (NC State) researchers enables artificial intelligence models to be developed faster and more accurately. Federated learning involves multiple devices (clients) each using their own data to train local models and send updates to a centralized server to create a hybrid model that ideally performs better than the clients on their own. However, heterogeneity in the clients' data can result in local model modifications that hurt the hybrid model's performance. In the new approach, the central server is given more information about relevant data characteristics in the form of Jacobian matrices, which are input into an algorithm that generates an improved model. Said NC State's Ryan Pilgrim, "The algorithm not only sidesteps multiple communication rounds, but also keeps divergent local updates from degrading the model."

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A Yaskawa robotic arm processing small packages and letters at FedEx’s Memphis hub. Robots Aren't Done Reshaping Warehouses
The New York Times
Patrick Sisson
July 12, 2022


Companies are accelerating the deployment of robots in warehouses, with experts anticipating a transformation in operations and design. Surveys conducted by the Material Handling Institute predict warehouse robot adoption will increase 50% or more in the next five years, with the goal of software- and artificial intelligence-guided robot teams moving packages and products seamlessly. E-commerce giant Amazon has helped lead this trend through its acquisition of robotics company Kiva Systems, and by deploying more than 500,000 robots. Demand for goods-to-person robots, or collaborative robots (cobots) that work alongside warehouse staff, is accelerating their adoption. Industry analysts also cite a tight labor market as driving interest in robots.

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The Exo programming language helps performance engineers transform simple programs that specify what they want to compute into very complex programs that do the same thing as the specification. A Programming Language for Hardware Accelerators
MIT News
Rachel Gordon
July 11, 2022


Massachusetts Institute of Technology researchers have created a programming language for writing high-performance code on hardware accelerators. The underlying concept of the Exo language is "Exocompilation," which externalizes responsibility for selecting which optimizations to apply, when, and in what order, from the compiler to the performance engineer. Exo also guarantees all the optimizations are correct. Cornell University's Adrian Sampson described the Exo language as “a compiler that's parameterized over the hardware it targets; the same compiler can adapt to many different hardware accelerators." The exocompiler also allows performance engineers to describe the new chips they want to optimize for, without having to alter the compiler.

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A U.S. Navy technician works on the new high-speed 3D printer on the USS Essex. U.S. Navy Uses 3D Printers to Turn Warships Into Weapons Factories
Popular Mechanics
Kyle Mizokami
July 12, 2022


The U.S. Navy has equipped the USS Essex amphibious assault ship with a high-speed three-dimensional (3D) printer to manufacture replacement parts for drones. The device can print metal components from materials such as aluminum which, according to a press release, means it can fabricate equipment like "heat sinks, housings, fuel adapters, bleed air valves, valve covers, and more." The 3D printer will be used to produce mission-critical parts as the technology advances, which is critical for older equipment that the manufacturer no longer makes. The military views such additive manufacturing technology as essential for supporting its forward-deployed forces.

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A 'Wise Counsel' for Synthetic Biology
Max Planck Gesellschaft (Germany)
July 8, 2022


Researchers at Germany's Max Planck Institute for Terrestrial Microbiology (MPI) and France's INRAe Institute have developed a modular software application for optimizing biological systems, which they said does not require computational skills to use. The researchers applied the Machine learning guided Experimental Trials for Improvement of Systems (METIS) software to various applications, including optimization of protein production, genetic constructs, combinatorial engineering of enzyme activity, and a carbon dioxide (CO2) fixation metabolic cycle called CETCH. MPI's Christoph Diehl said METIS can democratize and promote current biotechnology, synthetic biology, genetic circuit design, and metabolic engineering research, and also "can be a very helpful system for prototyping new-to-nature systems."

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A silicon-based switch that manipulates light through the use of phase-change material (dark blue segment) and graphene heater (honeycomb lattice). Next-Generation Datacenters Within Reach Thanks to Energy-Efficient Switches
University of Washington
July 6, 2022


A team of researchers led by University of Washington (UW) scientists has created a silicon-based non-volatile switch that manipulates light via a phase-change material and a graphene heater. The "set and forget" switch can maintain the flow of information without additional energy; pumping a current through the doped silicon causes a heat pulse that transforms the phase-change material, which remains in that state until another heat pulse returns it to its original state. The researchers found a graphene heater can reliably switch the doped silicon’s state over 1,000 cycles. "Compared with what is currently being used in datacenters to control photonic circuits, this technology would greatly reduce the energy needs of datacenters, making them more sustainable and environmentally friendly," explained UW's Arka Majumdar.

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Gender Bias in Search Algorithms Has Effect on Users
New York University
July 12, 2022


New York University (NYU)'s Madalina Vlasceanu and David Amodio found gender-neutral online searches return male-dominated output, promoting gender bias and potentially influencing hiring decisions. The researchers tapped gender inequality rankings for 153 countries in the Global Gender Gap Index, then determined whether words that should refer with equal probability to a man or a woman are more often male-affiliated through Google Image searches for gender-neutral equivalents for "person" across 37 countries. Those searches yielded a greater number of male images in nations with greater gender inequality, an indication that algorithmic gender bias dovetails with societal gender inequality. Said Amodio, "These findings call for a model of ethical AI [artificial intelligence] that combines human psychology with computational and sociological approaches to illuminate the formation, operation, and mitigation of algorithmic bias."

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Researchers Defeat Facial Recognition Systems with Universal Face Mask
Help Net Security
Zeljka Zorz
July 12, 2022


Researchers at Israel's Ben-Gurion University of the Negev (BGU) and Tel Aviv University found that facial recognition (FR) systems may be thwarted by fabric face masks boasting adversarial patterns. The researchers employed a gradient-based optimization process to generate a universal perturbation and mask to falsely classify each wearer as an unknown identity. BGU's Alon Zolfi said, "The perturbation depends on the FR model it was used to attack, which means different patterns will be crafted depending on the different victim models." Zolfi suggested FR models could see through masked face images by training them on images containing adversarial patterns, by teaching them to make predictions based only on the upper area of the face, or by training them to generate lower facial areas based on upper facial areas.

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Developmental psychologists test babies’ awareness of the basic physics of everyday objects. A research team at Google-owned company DeepMind developed a similar test for artificial intelligence. DeepMind AI Learns Simple Physics Like a Baby
Nature
Davide Castelvecchi
July 11, 2022


Computer scientists at the DeepMind artificial intelligence (AI) research laboratory trained a software model to learn simple physical rules about object behavior. The researchers trained the Physics Learning through Auto-encoding and Tracking Objects (PLATO) neural network model using animated videos and images of objects like cubes and balls, in order for it to generate an internal representation of the physical properties of each object. The model learned patterns such as continuity, solidity, and persistence of shape. DeepMind's Luis Piloto said the software makes predictions at every step in the video, and its accuracy increases as the video progresses. Piloto suggested PLATO could be a first step toward AI that can test theories about how human infants learn.

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Julie Raine, who has battled with trypanophobia (fear of needles), wears a VR headset in an attempt to overcome her phobia. New Zealand VR App Helps Conquer Phobias
The Guardian (U.K.)
Eva Corlett
July 12, 2022


oVRcome, a phone-based virtual reality (VR) application designed to treat phobias, successfully completed a six-week clinical trial, according to researchers at New Zealand’s University of Otago. Technology entrepreneur Adam Hutchinson, in consultation with clinical psychologists, developed a prototype of oVRcome, which relies on behavioral treatment exposure therapy to treat phobias by safely exposing a patient to an anxiety-causing situation. More than 100 participants have used the app to treat fears of needles, spiders, flying, heights, or dogs with a combination of mindfulness modules and virtual reality exposure therapy. Cameron Lacey at New Zealand's University of Otago said, "With virtual reality, you can be in your own home, be transported to an environment which has those feared stimuli—be it heights or spiders—in a predictable way, at your convenience."

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