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"An Israeli company is trying to prove that augmented reality is not only the premise of video games, it can also save lives. iOnRoad is a new mobile application, developed by Picitup, that is "helping smartphone users make smarter driving decisions" by using a phone's camera and GPS."

"HTTP/2 is a more modern protocol that essentially speeds web browsing up using new ways of transporting data between the browser and server across the internet. It is backwards compatible with HTTP1.1 and uses most of the same technologies, but it is more efficient and allows servers to respond with more content than was originally requested, removing the need for the user's computer to continually send requests for more information until a website is fully loaded."

"Now, the number of combinations of these columns grows exponentially with the number of columns. So if you have many, many columns-and we do in modern databases-you'll get up into millions and millions of attributes for each person. Now, if I start allowing myself to look at all of the combinations of these features-if you live in Beijing, and you ride bike to work, and you work in a certain job, and are a certain age-what's the probability you will have a certain disease or you will like my advertisement? Now I'm getting combinations of millions of attributes, and the number of such combinations is exponential; it gets to be the size of the number of atoms in the universe."

"One of Google's self-driving cars crashed into a bus in California last month. There were no injuries. It is not the first time one of Google's famed self-driving cars has been involved in a crash, but it may be the first time it has caused one. "

Much of current science deals with even more complicated systems, and similarly lacks exact solutions. Such models have to be "computational" - describing how a system changes from one instant to the next. But there is no way to determine the exact state at some time in the future other than by "simulating" its evolution in this way. Weather forecasting is a familiar example; until the advent of computers in the 1950s, it was impossible to predict future weather faster than it actually happened.

"But researchers at New York University's AI Now Institute have issued a strong warning against not only ubiquitous facial recognition, but its more sinister cousin: so-called affect recognition, technology that claims it can find hidden meaning in the shape of your nose, the contours of your mouth, and the way you smile. If that sounds like something dredged up from the 19th century, that's because it sort of is."

""My concern is that a facial recognition rejection can [create] bias," said Rudolph. "So, if someone has a lot of faith in this technology and thinks that it's foolproof, and someone is rejected by this system, that customs officer or gate agent may be predisposed to saying this person is traveling with fraudulent credentials. That's a crime and a serious issue.""

"People in Soho, Piccadilly Circus, and Leicester Square are being told by the London Metropolitan Police to submit to a trial of the force's notoriously inaccurate, racially biased facial recognition system, which clocks in an impressive error-rate of 98% (the system has been decried by Professor Paul Wiles, the British biometrics commissioner, as an unregulated mess)."

" Critics have pointed out that the old computing adage "garbage in, garbage out" also applies to ML. If the data from which a machine "learns" is biased, then the outputs will reflect those biases. And this could become generalised: we may have created a technology that - however good it is at recommending films you might like - may actually morph into a powerful amplifier of social, economic and cultural inequalities."

""In some ways we've lost agency. When programs pass into code and code passes into algorithms and then algorithms start to create new algorithms, it gets farther and farther from human agency. Software is released into a code universe which no one can fully understand.""

"The county is plotting the course to replace an enterprise resource planning system that has been in place since the 1980s."

"is an experimental service from Carnegie Mellon University that stores images of old processors, as well as the old operating systems that ran on top of them, along with software packages for those old OSes; this allows users to access old data from obsolete systems inside simulations of the computers that originally ran that data, using the original operating systems and applications."

"FOLLOW US Twitter / Facebook / RSS Machine learning image classifiers use context clues to help understand the contents of a room, for example, if they manage to identify a dining-room table with a high degree of confidence, that can help resolve ambiguity about other objects nearby, identifying them as chairs. The downside of this powerful approach is that it means machine learning classifiers can be confounded by confusing, out-of-context elements in a scene, as is demonstrated in The Elephant in the Room, a paper from a trio of Toronto-based computer science academics."

"Customers will be able to use a "Smile to Pay" facial recognition system at the tech-heavy, health-focused concept store, part of a drive by Yum China Holdings Inc to lure a younger generation of consumers. "

"Affectiva is running a program that pays drivers to help train its emotion-recognition system. The company sends drivers a kit including cameras and other sensors to place within their vehicles. These record a person's facial expressions, gestures, and tone of voice on the road. That data is then labeled by trained specialists for a range of emotions, and fed into deep neural networks."

"The platform's automated tools may have mistaken the visuals of the burning building for 9/11 footage, according to Vagelis Papalexakis, an assistant professor of computer science and engineering at the University of California, Riverside who studies machine learning used in similar systems."

"The facial recognition system is currently being rolled out across six of Prof Shen's classes. "The new system saves time and reduces the workload of students," Prof Shen told the Beijing News. "Out of one hundred students, it usually only fails to recognise one student." But obviously, not everyone is a fan."

""The problem," Leveson wrote in a book, "is that we are attempting to build systems that are beyond our ability to intellectually manage.""