Shri Narayanan, from the University of Southern California, has developed a new program that runs facial recognition software and voice recognition software simultaneously to analyze gender bias in high-grossing box-office films. This program has analyzed 300 films, and the study shows that women are underrepresented on the big screen. Narayanan is also using machine learning and natural language processing to evaluate film scripts, to explore further biases.

A virtual-reality training system currently in development by Exeter-based researchers and experts from the nuclear power industry could help prevent accidents in high-risk jobs. Employees using the system could gain experience with high-stress tasks in a safe environment, while employers could use the eye tracking and physiological sensor data to better understand how workers learn and how they react under pressure.

Twitter is making efforts to crack down on harassment on their platform using several strategies: enhancing the Mute feature with new screening options, increasing automatic flagging of potential abuse, and trying to be more transparent about how they handle harassment. By reducing harassment, Twitter hopes to increase its user base and attract more investors.

Brown’s Humans to Robots Lab has developed an algorithm to reduce the errors a robot makes when it fetches an object. The robot asks questions and draws inferences from the answers, to make the correct decision on what object to fetch. The goal is to make robots more helpful to humans.

The federal government is attempting to bridge the growing digital divide in low-income families by expanding a subsidy program, Lifeline, to include broadband Internet access. The Federal Communications Commission’s main goal in revising Lifeline is to address the increasing number of students without online access needed to complete schoolwork and homework. Other methods are being used to in an effort to patch this divide, such as wifi-equipped buses and school-provided wireless hotspots.

Researchers from the University of Manchester have demonstrated that it is possible to build a super-fast self-replicating computer. Because it is composed of DNA molecules rather than electrical circuitry, when presented with a choice, such a computer can replicate itself to simultaneously compute the solutions. Demonstrating that this (previously only theoretical) machine is physically possible opens up new possibilities in the future of scientific computing.

Human clinicians are known not to be very accurate at predicting suicides, so researchers are developing machine-learning algorithms that use multiple factors to identify short-term suicide risk. Data scientists trained the algorithm on data from thousands of clinical records, from both non-fatal suicide cases and random patients. Accuracy was significantly better than studying only one risk factor at a time. Using such a system could aid clinicians in targeting at-risk patients and treating them early.

Jiebo Luo and Yu Wang are using Twitter data to develop models that would correctly predict the result of the 2016 presidential election. They are analyzing Twitter data from the candidates’ followers with machine learning to identify trends that correlate with events and changes during the campaigns, and with the final results.

Researchers at the University of North Carolina, Chapel Hill have applied deep-learning algorithms to brain scans of children with a high risk of autism. Algorithms used three indicators, brain surface area, volume, and the gender of the child, to determine if 6- to 12-month-old infants were likely to develop autism. The results were 81% accurate at predicting later diagnosis. This improves over a 50% prediction rate from behavioral questionnaires.

Google Alphabet has developed new software called Perspective that will flag potentially problematic user comments, for example so news sites can narrow down which posts require manual review. A machine-learning algorithm was given thousands of comments rated for toxicity, in order to build a model that could identify the problematic ones. The developers hope that this system will enable more sharing of thoughts and ideas.

Interference from subatomic particles could be the cause of serious computer malfunctions at the hardware level. A single-event upset, or SEU, can disrupt microelectric circuitry, altering data or causing system failures.

The University of Plymouth has developed ICAlert, an easy-to-install device that monitors network traffic and sends alerts if users try to access dangerous web content (such as child pornography or terrorist sites). They aim to make browsing safer for children and teens by providing the devices and software to schools at a low cost.

Doña Ana Community College (DACC) and Virgin Galactic are teaming up to create a new educational outreach program. The partnership focuses on new virtual reality (VR) technologies and explores how they might be used in various settings and applications. It will begin with students using a VR simulation to learn concepts in aerospace technology.

Toyota is investing 50 million dollars and partnering with Stanford University and the Massachusetts Institute of Technology (MIT) to develop artificial intelligence and robotics technology needed for advanced driver-assistance systems. While Toyota is not trying to develop a fully automated car, they note that incremental advances in such driver-aid systems could eventually lead to driverless smart cars.

Dutch researchers have discovered a method of hacking commonly used microprocessors. Operating systems randomly assign the locations in memory where programs run, but this hack detects where a program is running, making bugs easier to exploit. If hackers figure out how to use this method, it could expose millions of computers to attacks — as it is impossible to fully fix with software updates alone.

Technology companies, such as Facebook and Google, are developing artificial intelligence systems (AI) for mobile devices to improve the privacy of messaging applications. New AI innovations allow algorithms that need less computing power, and can therefore be implemented locally on mobile devices. This means that information would not be sent to and from the cloud, reducing potential security issues.

A chip, designed by MIT researchers, may reduce the level of energy required to use speech recognition. The software specific speech recognition chip will use up to an estimated 99% less energy compared to universal software compatible chips. The researchers hope to provide an energy efficient solution that allows users to interact with their small electronic devices using speech instead of touch based user interfaces.

Research from the Salk Institute for Biological Sciences suggests that an algorithm used for managing the flow of information on the Internet may also be at work in the human brain. This kind of insight could improve our understanding of neural networks in the brain, including how learning disabilities work.

University of Toronto researchers have developed algorithms which can efficiently generate an accurate 3D image of a protein molecule from several 2D images in just a few minutes. This advance has far-reaching implications for the medical field. For example, drug researchers will be able to use these 3D protein models to analyze the structure of disease-specific proteins and predict the way experimental medications will bind to those proteins inside the body.

Researchers from Tel Aviv University and Ben-Gurion University have developed new software that will allow smartwatches to verify handwritten signatures. This software monitors the movement of the entire wrist in order to catch attempts at forgery, by identifying movements that do not match the movements of the original owner. The goal of this software is to reduce acts of forgery.

Researchers, led by WorldPop at University of Southampton and Flowminder Foundation, have developed a way to measure poverty levels in Bangladesh. They combine anonymous mobile phone data, such as data usage and distances traveled by the phone’s user, with satellite sensor data such as use of electric lights. They hope to provide more precise data about poverty levels to help governments and relief organizations combat poverty.

Research performed at the University at Buffalo has suggested that the swelling of subway usage during large events correlates closely with increases in Twitter activity. The Twitter data, which can be filtered by location and content, could potentially become a cost-effective aid to event planning and transit scheduling for crowded occasions.

A number of companies are beginning to use artificial intelligence to compose music. For example, music can be generated using artificial neural networks that learn the structure of human-generated music, then produce new instances. This article focuses on the start-up Jukedeck, but also covers several other companies, including Google and IBM, that are creating their own music-generation AIs — each with different approaches. These developments have the potential to create a new dynamic in the music industry.

Georgia Tech Researchers have created an early prototype system that uses a language model to predict the perceived credibility of social media messages, for example based on key mood words. This prototype system could lead to an application to help users identify credible information on social media.

Private medical data is a multi-million dollar industry that is growing rapidly, according to Adam Tanner at Harvard’s Institute for Quantitative Social Science. When medical data is initially sold to big data miners, it may be referred to only by unidentifiable numbers. However, data miners can re-identify patients by cross-referencing the medical data with data collected from other sources.

Researchers at MIT are conducting a worldwide survey to determine how consumers think a self-driving car should handle morally complex situations. Their findings will tell designers how drivers will generally expect their self-driving vehicles to react, and what might need to be added so that potential buyers can better trust the new technology.

A team of researchers at Stanford University has developed an artificial intelligence (AI) algorithm that can identify early symptoms of skin cancer. The researchers trained the algorithm with a large data set of images that had already been identified as cancerous or benign. The algorithm identifies skin lesions with the same accuracy as board-certified dermatologists.

Researchers developed an app that suggests news stories using locally stored personal data. They are investigating ways to provide services to users without storing their personal information in remote servers, as a solution to privacy issues with news apps.

The European Parliament is considering a proposed legal framework to define the rights and responsibilities of autonomous artificial intelligences and of the companies and engineers who make them, including who is responsible for errors and who benefits from products created by AIs. The framework also suggests measures to reduce the negative economic impacts on the human labor force.

A group of UK Internet service providers are attempting to crack down on piracy by sending emails to users of peer-to-peer services who have been flagged for piracy. The emails inform users about legitimate ways of acquiring content. Some argue that this is “too little, too late”, and that monitoring P2P traffic is not sufficient since many pirates now use direct downloads and streaming, which are not monitored.

“Sight Machine”, a performance piece by artist Trevor Paglen, uses AI to generate a live image mapping of musicians as they play. The algorithm involves movement-analysis techniques common in automated surveillance. By showing how machines see movement, Paglen hopes to highlight the distinct divide between how AIs and humans perceive things — and how that might affect computer-aided decision-making.

Kaspersky Lab held a contest for researchers exploring the use of blockchain accounting to verify electronic voting. The goals included secure methods of counting votes and managing transactions.

China is seeking to prototype an exascale computer (capable of a billion billion calculations per second) by the end of the year, thereby ensuring the country’s position as a world leader in supercomputing. The calculation speed and data transmission efficiency of this system would have far-reaching implications in enabling big data analysis and cloud computing.

The UK’s Medical Research Council is testing new AI software that will aid in predicting when a person with a heart disorder might die. The technology uses MRI scans of different parts of the heart to tell whether the organ will fail. As a result, it could find patients who need more extreme treatment, and possibly help save lives.

Romanian border police are using a system designed by the University of Arizona called AVATAR (Automated Virtual Agent for Truth Assessments in Real-Time), to screen international travelers at a Bucharest airport. The system is intended to measure body language, verbal responses, and physiological conditions before providing a summary for human personnel. Results from testing in Bucharest could influence whether and how the AVATAR system is implemented in the future.

Georgia Technical University is working on ways to improve Jill Watson, an artificial intelligence system that fills the role of a virtual teaching assistant. The goal of this project is to increase efficiency of online student assistance.

Fukoku Mutual Life Insurance, an insurance firm in Japan, is replacing 34 workers with an AI system that will calculate payouts to policyholders. They are making these changes in an attempt to increase productivity within the firm. The article mentions other new uses of AI systems in Japan, including in government and politics, intended to increase productivity.

Cybersecurity researchers recently discovered that ultrasound cross-device tracking (uXDT), in which a web page plays an ultrasound signal that prompts nearby devices to identify themselves via ultrasound, could be effective even when users are using the anonymization proxy Tor. This provides an example of the continual arms race between privacy-enhancing technologies and privacy-invading technologies.

Alexa, Amazon’s voice-operated artificial intelligence assistant, is becoming more widely used in a variety of products, as more companies build and implement Alexa-based systems. This allows people to control items like their cars, refrigerators, or home climate control systems with just their voice, often remotely.

A team of engineers from Harvard University have created a robot named Root, along with a multi-language coding environment to program it. Their goal is to provide a cost-effective learning tool that will teach people of all ages how to code.

Fake news stories shared on social media played a major role in the spread of misinformation during the 2016 U.S. elections and after, even spurring individuals into taking dangerous action. Google and Facebook have pledged to discourage known fake news, for example by limiting advertising. However, many argue for more fundamental measures, to address the underlying issue that services like Facebook are built around showing users what they want to see.

Uber has acquired an artificial intelligence (AI) startup, Geometric Intelligence, and put the team to work on (among other things) self-driving cars. The company already uses machine learning to predict when and where cars will be needed, but self-driving cars would be a significant boon for company profits — albeit at the expense of existing drivers working with Uber.

Mojang, Microsoft, and Code.org are teaming up to inspire a new generation of coders. The latest version of Code.org’s Hour of Code is a tutorial that allows beginner coders to create and share their own Minecraft game. Code.org’s goal is to provide “every student in every school…the opportunity to learn computer science” — in this case, through the highly popular Minecraft game.

Technical University of Munich researchers have created a project named OpenGridMap that maps the locations of electrical infrastructure (part of OpenStreetMap). Their goal is to build a worldwide map system plotting the information, which will be accessible to all engineers and scientists.

Researchers at the University of Toronto are working on a program that analyzes an image and then produces music based on the contents of that image. In an early demonstration of the capabilities of the AI, it produced a holiday-themed song based on a picture of a Christmas tree. This demonstrates that computers have the potential to create music could be in many ways similar to what humans would produce when given the same theme.

Researchers at Griffith University successfully predicted the winner of the 2016 presidential election, including the outcomes in 49 out of 50 states, using data collected from social media interactions. The prediction ran contrary to general expectations based on polling, suggesting that more accurate election predictions can be obtained by analyzing social media interactions — which requires large-scale data analytics.

Industry leaders and computer scientists are pushing for more use of machine intelligence so that machines can aid doctors, business corporations, investors and many more entities in decision making. The article discusses the potential rewards of using machine intelligence to solve real-world problems, for example, whether machine learning can help to better quantify uncertainty when trying to predict outcomes in various fields.

The researchers at Google have trained an AI how to lip-read TV shows. Such an AI system could be used to help humans communicate with computers — including perhaps when they did not intend to.

HitchHike, a proposed low-energy wireless radio from a research team at Stanford, seeks to provide a power-efficient method of communication between Internet of Things devices and a wireless network. The device could be driven by a small battery for a decade or more, and even has the potential to harvest energy from radio waves, allowing it to possibly be powered without a battery. This kind of innovation would make IoT development much more feasible — meaning many more of the devices around us could soon be communicating and collecting data.

The Investigatory Powers Act, recently passed in the UK, will require telecom companies to store records of phone calls and websites visited for up to a year, and give authorities access to the latter without a warrant. It also legalizes bulk data collection by the British government. Groups like the Open Rights Group and Privacy International are openly critical of this law, calling it draconian.

At a Computing IT Leaders Forum, panelists discussed the potential of software-defined storage (SDS) to help companies avoid vendor lock-in and allow more flexibility in planning — an issue given how quickly data storage technology changes. The article also mentions how SDS provides an alternative to cloud storage, as the latter raises concerns about data security.

Researchers from Jiao Tong University in China have applied facial recognition algorithms to guess whether a person has a criminal history based upon their unique set of facial features. The algorithms achieved nearly 90% accuracy. Questions arise around the legality and ethics of how such a technology might be applied.

A patient suffering from ALS (Amyotrophic Lateral Sclerosis) at UMC Utrecht, a hospital in the Netherlands, recently received a brain implant that allows them to remotely operate a speech computer with their mind. The patient can use this computer to communicate with their friends and family at home. If initial trials prove successful, the implants could see larger, international trials which lead to the development of even more advanced implants.

Researchers from Columbia University and a Brazilian think tank have developed a machine-learning algorithm to predict whether now-declassified U.S. State Department cables from the 1970’s were unclassified, limited official use, confidential, or secret, based on contents and metadata such as sender and recipient. The study provides insight into how the information was classified, but also carries potential national security implications by highlighting trends in erroneous information classification — and systematic gaps where secret cables should have been declassified.

Researchers from MIT’s CSAIL and Stony Brook University are researching ways to make using multi-core computers easier. They have created a method for describing, in general terms, the computation task desired, and then automatically converting this to a parallelized program. This makes it easier for domain experts (such as computational biologists or cybersecurity experts) to quickly write programs to support their research or tasks, without having to be parallel-programming experts as well.

Carnegie Mellon University has announced it will create a new research center to explore the ethics of artificial intelligence. This topic has increasing importance due to recent rapid progress in computing and robotics, including computer vision and speech recognition, with applications such as self-driving cars.

Computer scientists from UCLA have developed a secure, one-way communication technique similar in concept to mailing a lock box and later mailing the key to open the lockbox. The technique was developed to ensure messages sent over a network are not altered. The new innovation has wide applications that could benefit many businesses.

The Verge discusses the possibility of election machine hacking, along with other factors that could affect vote tallying and the results of an election.

As engineering progress slows, scientists try to find creative solutions to provide cheaper and faster computer chips. Researchers are attempting to create computer chips that use less power, via various algorithms, and reinvest that saved power into faster or more powerful computing abilities.

The Eclipse Science Working Group has released five software projects focused on accelerating scientific progress via computing. The open-source projects make new solutions in data analysis and other science-rich computational fields available for free to anyone who wants them.

Researchers at Rice University are investigating whether the use of “inexact computing” can make supercomputers more energy efficient. They are seeking to optimize calculation speeds and decrease the power input needed to yield high-quality solutions.

Artificial intelligence has recently been used to predict (past) judicial decisions in the European Court of Human Rights to a surprising degree of accuracy. This method could potentially be used to automatically identify cases that are likely to involve human rights violations, and is also an interesting example of how artificial intelligence can quantify and even predict human behavior based on pattern recognition.

Researchers have developed a system that estimates how safe visitors will perceive an area to be based on photographs of the area. The researchers began with a crowdsourcing effort to build an initial database of images and safety ratings of the area in the image. Over 1.4 million responses have then been used to train a machine-learning algorithm to identify these aspects automatically.

A recent large scale DDoS (distributed denial of service) attack on DNS provider Dyn caused many sites to become temporarily inaccessible, including Twitter, Spotify, and a number of other important social media, e-commerce, news, and code-sharing sites. The attack was coordinated using a large group of compromised devices known as a “botnet”. Rather than computers, much of this botnet consisted of infected IoT (Internet of Things) devices such as security cameras.

Twitter, Facebook, and Instagram have revoked commercial access to their data by social-media analysis company Geofeedia, which had been providing information obtained on their websites to police. The article discusses questions about the legality of preemptive data collecting on social media and how this information is used.

Researchers at the Indian Institute of Technology are focusing on a new strategy for recognizing sarcasm automatically. This development represents a step forward in helping computers to derive meaning from words.

An EFPL team is developing light robots called Soft Muscle, aiming to improve robot design. The EPFL team’s ultimate goal in developing Soft Muscle is to provide inexpensive exoskeleton designs that will assist in creating lighter, more flexible robots for any application.

The University of Arizona is using big data to help resolve public transportation issues in Fortaleza, Brazil. The algorithms they have created help identify problem areas that need more buses, bus lanes, or bus stops.

Through the use of VR (Virtual Reality), scientists seek to lower the cost and increase the availability of mental health care. They use VR technologies to help patients overcome their fears in a safe environment, by creating simulated situations that reproduce their fears. The availability of this treatment is increasing due to the lower costs of VR devices. The success of the VR experiments might potentially lead to higher quality and more accessible mental health care.

Scientists attempt to understand how computers think and learn in order to verify the reliability of large scale data analysis. This article covers several efforts in the last few years to understand how deep neural nets work. If scientists can understand how computers gather and interpret data in deep learning, these techniques can be used with more confidence, in day to day applications as well as in cutting edge scientific research.

Engineers at Google are upgrading their Google Translate service to use deep learning, which is an artificial intelligence technique. This is the first time this translation method has been used in a large production environment. The update greatly improves the accuracy of translations, increasing Google Translate’s ability to facilitate communication between speakers of different languages.

The CIA and their new Directorate of Digital Innovation are working on “anticipatory intelligence” to predict future events. The Deputy Director says that they can sometimes forecast outbreaks of unrest up to five days ahead. These predictions are made by using classified information as well as open source data; commentators speculate that much of the data comes from massive social media surveillance.

The contract that specified the U.S. government’s oversight over Internet address assignment has expired and ICANN (an international NGO) now has full control. ICANN holds the responsibility to protect the integrity, freedom, and security of the domain name system and IP address assignment. ICANN’s decisions thus have the potential to affect the communications of Internet users around the world.

The NFL began placing tracking sensors inside of footballs and shoulder pads during the preseason and will carry this practice into Thursday night games this season. The sensors will allow the league to collect data on areas such as player speed, throwing strength, and positioning. This development will lead to even more growth in the constantly burgeoning field of sports analytics, impacting the way that player performance is evaluated.

With the help of crowdsourced data, Google AI’s image recognition algorithms are achieving greater accuracy. Objects in photographs are now more accurately described, and are interrelated with other objects in auto-generated captions. With the increase in photo-captioning accuracy, more questions arise about privacy online and on social media.

A new exoskeleton design seeks to lower the recovery time for stroke victims in rehabilitation. Researchers are investigating the exoskeleton design to observe whether patients can use their mind to perform basic actions with their numb limbs. The exoskeleton design provides a more natural path towards recovery through reintegrating the use of paralyzed limbs.

Google’s new messaging app, Allo, has been criticized because the default settings provide substantially less privacy than Google had previously announced they would. In part, this is to provide more training data for a “smart reply” feature that generates suggested responses. When messages are stored, law enforcement agencies will be able to access them with warrants.

Researchers are planning to develop software that can monitor and gather data on the performance and efficiency of a marine vessel. Through the use of machine learning, this data would then be applied to create an ideal balance between efficient performance and ship integrity, lowering maintenance and operational costs.

New York City police used the Wireless Emergency Alert system recently to send out a “Wanted” text message about a bombing suspect, and they plan to use the system for similar purposes in future. However, they have received heavy criticism, mainly saying that the short, pictureless message may have encouraged mass racial profiling, and that overuse of the system might lead to people ignoring it.

Beyond tech companies such as Amazon and Google, big data has a significant effect on science, engineering, and even plumbing. As the government in Flint, Michigan has worked to correct the dangerous levels of lead contamination reported earlier this year, researchers at the University of Michigan have aggregated and analyzed data for homes in the area. Their analysis is providing new insights into how the government can best direct their efforts, to reduce costs and increase impact.

Facebook recently blocked a news article that reprinted a Vietnam War photo of a naked girl running from a napalm attack. The photo was flagged by an algorithm designed to identify photos containing nudity. Facebook keeps changing how much it uses humans vs. algorithms to control news feeds; trouble ensues either way. The issue raises questions about whether Facebook acts — or should act — as a media company with editorial responsibility or as a neutral distributor.

An interdisciplinary research team developed a large dataset of 21,030 high-resolution satellite images of India labeled for whether they show built-up areas. The dataset can be used as input to algorithms for detecting urban areas; for example, the team used it to map urbanization in India. This allows scientists and governments to study changes in urbanization and industrialization over time.

The debate over net neutrality has largely focused on whether Internet service providers should allow some content providers to negotiate faster/cheaper access to their content for users. This article describes a prototyped system that would allow users to designate which content they want to special access to. Net neutrality has been seen as a digital divide issue; wide adoption of a user-choice system would change the parameters in that debate.

This article describes an early warning system for mudslides and flood in rural El Salvador that uses a mesh network of simple devices, within local villagers’ needs and cultural structures. The article can be used to highlight differences between the U.S., where a vast array of technological advances can aid in mitigating disasters, and remote areas of the world where many of the basic technologies involved, such as cell-phone networks, do not exist or are not reliable.

Beauty.AI developed a set of algorithms to judge photos according to five factors in human standards of beauty; it disproportionately chose photos of white people. The article discusses the potential consequences of emergent bias in algorithms and/or datasets in general, including more consequential examples like predictive policing.

The Brave web browser (released earlier this year) allows only ads that don’t track users from site to site; it has now added a feature to record how much time users spend on different sites and allow them to send micropayments to those publishers. The article raises examples of how the web has impacted the economics of media and publishing, and also touches on online tracking, data anonymization and de-anonymization, and even Bitcoin.

Researchers are using data on the locations people make calls from to model the movement patterns of Boston commuters; the system may replace or supplement surveys of residents. The article discusses the benefits of gathering and processing more data more quickly and cheaply, though students may be able to identify some disadvantages of using call data.

Hackers have broken into the Illinois and Arizona state boards of elections’ records, following hacks of the Democratic National Committee and the Clinton campaign in the last couple of months. This highlights concerns about the security of voter records and even ballot integrity, including effects on U.S. citizens’ confidence in election results.

Researchers have developed a machine-learning algorithm that achieves 70% recall in identifying depressed individuals by characteristics of their (pre-diagnosis) Instagram photo posts. This is a great example of a medical development with great potential for benefit (early diagnosis and treatment) that also raises serious concerns (privacy, misuse of the information, misprediction). It’s also an example of Mechanical Turk being used as a research platform.

Twitter announced that it has increased the rate at which it is suspending accounts the service identifies as promoting terrorism, and is working on ways to block the same users from opening new accounts. In addition to highlighting how important social media has become in political and social movements (including violent ones), this raises questions about censorship and about companies’ right to control what their platforms are used for.

Data scientists used post metadata and patterns in post format to show that tweets from @realDonaldTrump come from different people, and sentiment analysis to show that the tweets from Trump himself differ in tone. By identifying patterns in public communications, they found information that was (presumably) not supposed to be public.

The U.S. National Security Agency (NSA) has been using an exploit in Cisco firewall software to break encryption and spy on traffic in Virtual Privacy Networks (VPNs). In the Internet age, government surveillance is more about collecting torrents of data to sift through than about focused operations, which affects businesses’ standards about when they protect communications and how.

Stories told as a stream of text messages between the characters, delivered by story apps, are gaining in popularity (especially for YA horror/suspense). Texting has enabled the creation of a new genre, but the author points out similarities with older genres similarly defined by their delivery mechanisms.

The U.S.’s Federal Source Code Policy was recently revised to require that all custom code created or commissioned by government agencies must be available to all other agencies, and that 20% of it must be released open source. This emphasizes how integral software is to government operations, and offers an opportunity to remind students about how open source software works.

Patients using brain-machine interfaces to control robotic prosthetics, along with virtual-reality devices that simulated moving their own limbs, were unexpectedly able to regain some actual control of their own limbs, apparently reengaging their spinal cord nerves. Includes a short description of computational modeling of how the brain controls movement.

Using standard data already collected by most airplanes, researchers are testing and refining turbulence-modeling algorithms that promise to greatly improve detection and prediction, so that pilots can avoid trouble spots.

Researchers at MIT and Indiana Univerity are developing differential privacy techniques that add a small amount of random noise to queries on large genetic databases. This means databases can be made more openly available without (as much) risking the privacy of the individuals whose genetic data is in them. Includes a description of the potential privacy attacks being mitigated, and notes the scientific consequences of having to worry about privacy-compromising attacks on health databases.

Countries in Europe are developing a unified cloud-based data platform, to be used by services that provide real-time information about transit and parking. Their goal is to make it easier for commuters to use the fastest, most efficient, most environmentally sustainable transit options.

Researchers at Bielefeld University have created a system that translates water pressure data into sound, helping swimmers improve their their technique by getting live feedback about their movements. An example of how computing technology affects how people approach the task of improving sports performance.