In transportation applications such as real-time route guidance, ramp metering, congestion pricing and special events traffic management, accurate short-term traffic flow prediction is needed. For this purpose, this paper proposes several novel \textit{online} Grey system models (GM): GM(1,1$|cos(\omega t)$), GM(1,1$|sin(\omega t)$, $cos(\omega t)$), and GM(1,1$|e^{-at}$,$sin(\omega t)$,$cos(\omega t)$). To evaluate the performance of the proposed models, they are compared against a set of benchmark models: GM(1,1) model, Grey Verhulst models with and without Fourier error corrections, linear time series model, and nonlinear time series model. The evaluation is performed using loop detector and probe vehicle data from California, Virginia, and Oregon. Among the benchmark models, the error corrected Grey Verhulst model with Fourier outperformed the GM(1,1) model, linear time series, and non-linear time series models. In turn, the three proposed models, GM(1,1$|cos(\omega t)$), GM(1,1$|sin(\omega t)$,$cos(\omega t)$), and GM(1,1$|e^{-at}$,$sin(\omega t)$,$cos(\omega t)$), outperformed the Grey Verhulst model in prediction by at least $65\%$, $16\%$, and $11\%$, in terms of Root Mean Squared Error, and by $82\%$, $58\%$, and $42\%$, in terms of Mean Absolute Percentage Error, respectively. It is observed that the proposed Grey system models are more adaptive to location (e.g., perform well for all roadway types) and traffic parameters (e.g., speed, travel time, occupancy, and volume), and they do not require as many data points for training (4 observations are found to be sufficient).

AI is already widely used to gauge consumer sentiment. Amazon mines huge amounts of data about search and online purchasing behavior to uncover insights about what customers buy and predict what they might want to buy in the future. Netflix bases its movie recommendations on what you've watched in the past, for how long, and how favorably you review the show. In all of those cases, consumer sentiment is being gauged not by what consumers say they want but by their actual behavior. That's a crucial difference, and one that gives AI a significant advantage over traditional polls.

Nitrogen dioxide (NO2) is an important air pollutant formed during the combustion of fossil fuels. The reduced human activities in the wake of the COVID-19 pandemic led to sharp reductions in surface NO2 around the globe. Near-real-time NASA computer simulations, combined with surface observations, can be used to track the decline and subsequent recovery of NO2 related to COVID-19 stay-at-home orders around the globe. Since NO2 concentrations are a good proxy for industrial, transportation, and domestic activities, the changes in NO2 derived from NASA models during mandatory quarantine correlate well with officially reported changes in economic output. Observations from 4,778 air quality monitoring sites in 46 countries are used to monitor the change in NO2 as a result of COVID-19 containment measures.

As technologists and artists in new media (that strange place where words, imagery, meaning and new tech collide), we design, build, and test software experiences and products that center the deep creative impulse of humanity, because we are interested in the power of that impulse. We've observed throughout our work that many computing and AI software and tools have underestimated, and even excluded, this human impulse from their design. The particular joy of uncovering patterns and logic embedded in various functions of the universe, and building things that make use of them for people to enjoy, is unparalleled. It's no surprise that as computing devices became more accessible and explainable, people fell in love with them. But today, many are becoming uncomfortable with their ubiquity and feel less understood and more constrained by computing and AI, and that they must fight or compete with the software and products sold to them.

This article is part of the Free Speech Project, a collaboration between Future Tense and the Tech, Law, & Security Program at American University Washington College of Law that examines the ways technology is influencing how we think about speech. What could be one of the most consequential First Amendment cases of the digital age is pending before a court in Illinois and will likely be argued before the end of the year. The case concerns Clearview AI, the technology company that surreptitiously scraped 3 billion images from the internet to feed a facial recognition app it sold to law enforcement agencies. Now confronting multiple lawsuits based on an Illinois privacy law, the company has retained Floyd Abrams, the prominent First Amendment litigator, to argue that its business activities are constitutionally protected. Landing Abrams was a coup for Clearview, but whether anyone else should be celebrating is less clear.

Chinese state media with optimistic tone after Biden win. In a detailed policy document, President Trump's State Department is warning the incoming administration that it must address a Chinese government intent on displacing the United States as the world's foremost power. "The Trump administration achieved a fundamental break with the conventional wisdom. It concluded that the CCP's [Chinese Communist Party's] resolute conduct and self-professed goals require the United States and other countries to revise assumptions and develop a new strategic doctrine to address the primacy and magnitude of the China challenge," according to the document. The State Department's policy planning office, often called the department's "think tank," wrote the report as a long-term document to "sketch a framework for the fashioning of sturdy policies that stand above bureaucratic squabbles and interagency turf battles and transcend short-term election cycles."

A machine learning algorithm has shown the ability to link specific behaviors, such as walking and breathing, to their related brain signals – a first step to developing brain-machine interfaces. The algorithm, funded by the US Army, was tested on two monkeys that made various arm and eye movements. The technology successfully isolated the neural patterns in each of the animal's brain signals and determined which control these specific movements. The brain decoding algorithm could be designed to restore lost functions in those suffering with neurological and mental disorders. Although the algorithm is still in the development phase, the team sees it being used in brain-machine interfaces.

Decades of technological change have polarized the earnings of the American workforce, helping highly educated white-collar workers thrive, while hollowing out the middle class. Yet present-day advances like robots and artificial intelligence do not spell doom for middle-tier or lower-wage workers, since innovations create jobs as well. With better policies in place, more people could enjoy good careers even as new technology transforms workplaces. The report, "The Work of the Future: Building Better Jobs in an Age of Intelligent Machines," was released today, and the task force is hosting an online conference on Wednesday, the "AI & the Future of Work Congress." At the core of the task force's findings: A robot-driven jobs apocalypse is not on the immediate horizon.

Reconnaissance robots that can be lobbed 148 feet over walls, or into buildings and caves to provide real-time video have been tested by the Royal Marines. The 43 Commando Fleet Protection Group have been trialling the'throwbots' -- and other advanced kit -- during exercises around and in the tunnels beneath Gibraltar. The bots are built to survive falls of up to 32 feet, automatically self-right after landing and can operate for 30 minutes when submerged under 3 feet of water. Marines could throw the robots into unknown or occupied territory in order to get an advanced'lay of the land' without putting themselves directly at risk. When not testing new field tech, 43 Commando's responsibilities include protecting the UK's nuclear weapons arsenal at Her Majesty's Naval Base, Clyde, in Scotland.

In the early two-thousands, Merlin Mann, a Web designer and avowed Macintosh enthusiast, was working as a freelance project manager for software companies. He had held similar roles for years, so he knew the ins and outs of the job; he was surprised, therefore, to find that he was overwhelmed--not by the intellectual aspects of his work but by the many small administrative tasks, such as scheduling conference calls, that bubbled up from a turbulent stream of e-mail messages. "I was in this batting cage, deluged with information," he told me recently. Why was I having such a hard time?" In the nineteen-nineties, the spread of e-mail had transformed knowledge work. With nearly all friction removed from professional communication, anyone could bother anyone else at any time. Many e-mails brought obligations: to answer a question, look into a lead, arrange a meeting, or provide feedback. Work lives that had once been sequential--two or three blocks of work, broken up by meetings and phone ...