You probably assume that someone can only see what's on your computer screen by looking at it. But a team of researchers has found that they can glean a surprising amount of information about what a monitor displays by listening to and analyzing the unintended, ultrasonic sounds it emits. The technique, presented at the Crypto 2018 conference in Santa Barbara on Tuesday, could allow an attacker to initiate all sorts of stealthy surveillance by analyzing livestreams or recordings taken near a screen--say from a VoIP call or video chat. From there, the attacker could extract information about what content was on the monitor based on acoustic leakage. And though distance degrades the signal, especially when using low quality microphones, the researchers could still extract monitor emanations from recordings taken as far as 30 feet away in some cases .

New teachers, new backpacks, new crushes--and algorithms trawling students' social media posts. Blake Prewitt, superintendent of Lakeview school district in Battle Creek, Michigan, says he typically wakes up each morning to twenty new emails from a social media monitoring system the district activated earlier this year. It uses keywords and machine learning algorithms to flag public posts on Twitter and other networks that contain language or images that may suggest conflict or violence, and tag or mention district schools or communities. In recent months the alert emails have included an attempted abduction outside one school--Prewitt checked if the school's security cameras could aid police--and a comment about dress code from a student's relative--district staff contacted the family. Prewitt says the alerts help him keep his 4,000 students and 500 staff safe.

In June of last year, five researchers at Facebook's Artificial Intelligence Research unit published an article showing how bots can simulate negotiation-like conversations. While for the most part the bots were able to maintain coherent dialogue, the researchers found that the software agents would occasionally generate strange sentences like: "Balls have zero to me to me to me to me to me to me to me to." On seeing these results, the team realized that they had failed to include a constraint that limited the bots to generating sentences within the parameters of spoken English, meaning that they developed a type of machine-English patois to communicate between themselves. These findings were considered to be fairly interesting by other experts in the field, but not totally surprising or groundbreaking. A month after this initial research was released, Fast Company published an article entitled AI Is Inventing Language Humans Can't Understand.

The complaints add to the barrage of criticism facing the Silicon Valley giant over its handling of users' personal details. Several American government agencies are currently investigating Facebook's response to the harvesting of its users' data by Cambridge Analytica, a political consulting firm. Facebook's push to spread facial recognition also puts the company at the center of a broader and intensifying debate about how the powerful technology should be handled. The technology can be used to remotely identify people by name without their knowledge or consent. While proponents view it as a high-tech tool to catch criminals, civil liberties experts warn it could enable a mass surveillance system.

Two years ago, Sanjaya Wijeratne--a computer science PhD student at Wright State University--noticed something odd in his research. He was studying the communication of gang members on Twitter. Among the grandstanding about drugs and money, he found gang members repeatedly dropping the emoji in their tweets. Wijeratne had been working on separate research relating to word-sense disambiguation, a field of computational linguistics that looks at how words take on multiple meanings. The use of jumped out as a brand new problem.

Two weeks ago Facebook released yet another glossy marketing infographic site and video touting how its state of the art technology, top engineers and teams of experts have made massive strides in conquering yet another scourge of the online world through the power of advanced algorithms. This past week its EMEA counterterrorism lead announced that its algorithms were now deleting 99% of all ISIS and al-Qaida terrorism content across the site. As with all of Facebook's announcements to date, neither of these proclamations made any mention of how often the algorithms that increasingly control its platform are wrong and whether they are actually right more often than they are wrong. After initially promising to provide a response, the company once again declined to comment on the false positive rates of its algorithms or why despite repeated requests it continues to refuse to release those numbers. Why is the company so afraid to talk about whether its algorithms are actually accurate?

A Portland woman recently told a local news outlet that her Amazon Echo device had gone rogue, sending a recording of a private conversation to a random person in her contact list. On Thursday, two senators tasked with investigating consumer privacy sent a letter to Amazon CEO Jeff Bezos demanding answers. In the letter, Republican senator Jeff Flake and Democratic senator Chris Coons, who serve respectively as chairman and ranking member of the Judiciary Subcommittee on Privacy, Technology and the Law, ask Bezos to explain how exactly the Amazon Echo device listens to and stores users' voices. The senators also seek answers about what the company is doing to protect users from having that sensitive information misused. The letter, which was reviewed by WIRED, comes in the midst of what Flake calls a "post-Facebook" world, referring to the data privacy scandal in which Facebook says the data of as many as 87 million Americans may have been misappropriated by a political consulting firm called Cambridge Analytica.

Who says you can't get smart playing video games? Although the idea of spending hours playing video games isn't usually recommended for humans to increase their intelligence, the realistic 3-D graphics and environments of many video games just might make video games the perfect learning tool for artificial intelligence. AI algorithms get smarter and learn to perform tasks by being fed enormous amounts of data. When you're on Facebook, this doesn't present a huge obstacle. Facebook creates huge data sets daily and also has the financial capability to close any gaps.

The 9th annual Augmented World Expo at the Santa Clara Convention Center, May 29th to June 1st, 2018, was a celebration of AR's progress. Watershed events, like the introduction of ARKit from Apple in September 2017, have spurred innovation. Mobile AR is very hot. Most of the glasses look dorky, though some are slimming down. The dorky ones were by far the most popular. The bigger story, however, is how fast the enterprise segment is growing as applications as straightforward as schematics on a head-mounted monocular microdisplay are transforming manufacturing, assembly, and warehousing. Tom Emrich, Programmer of AWE and a partner in Super Ventures, delivered his dramatic keynote AWE using motion capture technology. For AWE's co-founder and Executive Producer, Ori Inbar, the Conference was nothing less than a victory lap. With Microsoft and Qualcomm among the Gold Sponsors, there was a palpable smell of vindication in the air.

Apple describes its mobile devices as designed in California and assembled in China. You could also say they were made by the App Store, launched a decade ago next month, a year after the first iPhone. Inviting outsiders to craft useful, entertaining, or even peurile extensions to the iPhone's capabilities transformed the device into the era-defining franchise that enabled Uber and Snapchat. Craig Federighi, Apple's head of software, is tasked with keeping that wellspring of new ideas flowing. One of his main strategies is to get more app developers to use artificial intelligence tools such as recognizing objects in front of an iPhone's camera.