For the past two months, cyborg police officers have screened travellers passing through Zhengzhou railway station in China. The officers, wearing smart glasses with built-in face recognition, have caught seven fugitives and 26 fake ID holders already. According to local media, some of the fugitives were wanted for alleged involvement in human trafficking cases. Zhang Xin, at LLVision, the firm that developed the GLXSS Pro smart glasses, says the glasses are very light so the police officers can wear them all day. Feedback so far been positive, she says. …

We present a framework to learn privacy-preserving encodings of images (or other high-dimensional data) to inhibit inference of a chosen private attribute. Rather than encoding a fixed dataset or inhibiting a fixed estimator, we aim to to learn an encoding function such that even after this function is fixed, an estimator with knowledge of the encoding is unable to learn to accurately predict the private attribute, when generalizing beyond a training set. We formulate this as adversarial optimization of an encoding function against a classifier for the private attribute, with both modeled as deep neural networks. We describe an optimization approach which successfully yields an encoder that permanently limits inference of the private attribute, while preserving either a generic notion of information, or the estimation of a different, desired, attribute. We experimentally validate the efficacy of our approach on private tasks of real-world complexity, by learning to prevent detection of scene classes from the Places-365 dataset.

Tue 13 Feb 2018 11.00 EST Last modified on Tue 13 Feb 2018 11.01 EST Drones invoke varying perceptions, from fun gadget to fly in the park to deadly military weapons. In the future, they may even be viewed as a handy tool in the battle to fight climate change. Greenhouse gas emissions from the tra...

The 2018 release from the Unicode Consortium contains Emoji 11.0, which brings 157 new adorable little pixel blobs to the 2,666 that previously existed. The list includes people with red, curly, and no hair. You may have missed it, but ride-hailing service Uber has been locked in a legal battle against the Alphabet-owned, self-driving vehicle company, Waymo since January 2017. The case alleged that a Google engineer gave Uber trade secrets regarding self-driving car tech. It's a complex issue of intellectual property and it's likely not the last one like this we'll see.

If the idea of swarms of delivery drones dropping packages all over our cities started out as a joke, for some reason the punchline hasn't landed yet. Amazon applied for a patent in 2015 for a command center, like a beehive, plopped into your city, which isn't a worrying metaphor at all. Google has its own program in the works, which at least for the moment involves delivering burritos. Again, if this is a joke, it's got a very long fuse. Forget about the insane logistics of such a system for a moment, or if you'd even be keen on drones swarming your town.

This article contains mild spoilers for the first season of'Star Trek Discovery'. At its best, science fiction does more than just entertain, or ensure its cliffhanger is strong enough that you come back next week. The cool spaceships and robots are just the framework through which we explore the anxieties and morals of our society at large. And we're at such a febrile point in history that we need sci-fi to ground us in what's coming in the not-too-distant future. I've been preaching patience for a while now, but I don't think that I can defend Star Trek Discovery any further.

SAN FRANCISCO - For nearly a year, Uber and Google parent Alphabet clashed over settling a lawsuit Alphabet filed against the ride-sharing company, according to two people familiar with the discussions. Uber chose to gamble for a victory in court rather than compromise, a choice that led to a high-stakes public trial last week. Negotiations went right up to to the trial itself, when as recently as last week, Uber's board had rejected a settlement offer. Yet on Friday, just as journalists were settling into the packed courtroom after days of bruising testimony, Uber announced it was settling the case. The agreement gave Alphabet's self-driving car business Waymo a stake worth $244 million in the world's most valuable privately-held startup - and the right to vet Uber's self-driving technology.

For any client-facing business, the front-runners of the future will be those who can adapt to the changing needs of clients. This fact is now starting to sink in for the legal sector, who have been slow in embracing transformative technologies up until now. Indeed, some have commented that the working practices of many in the industry have changed little since the time of Charles Dickens. In their 2017 report on the sector, PwC claim that clients have long been frustrated with the rising cost and speed of legal service delivery and many have responded by taking more work in-house, by bringing individual lawyers in through'lawyer on demand' providers. Many believe that the time is ripe and that the "2020s will be the decade of disruption" as law firms increase investment in technology to automate tasks and improve decision making.

In Phoenix, cars are self-navigating the streets. In many homes, people are barking commands at tiny machines, with the machines responding. On our smartphones, apps can now recognize faces in photos and translate from one language to another. Artificial intelligence is here -- and it's bringing new possibilities, while also raising questions. Do these gadgets and services really behave as advertised?

Contracting is a common activity, but it is one that few companies do efficiently or effectively. In fact, it has been estimated that inefficient contracting causes firms to lose between 5% to 40% of value on a given deal, depending on circumstances. But recent technological developments like artificial intelligence (AI) are now helping companies overcome many of the challenges to contracting. The main challenge firms face in contracting arises from the sheer number of contracts they must keep track of; these often lack uniformity and are difficult to organize, manage, and update. Most firms don't have a database of all the information in their contracts – let alone an efficient way to extract all that data – so there's no orderly and fast way to, for example, view complex outsourcing agreements or see how a certain clause is worded across different divisions.