For the past five years, the hottest thing in artificial intelligence has been a branch known as deep learning. The grandly named statistical technique, put simply, gives computers a way to learn by processing massive amounts of data. Thanks to deep learning, computers can easily identify faces and recognize spoken words, making other forms of humanlike intelligence suddenly seem within reach. Companies like Google, Facebook and Microsoft have poured money into deep learning. And the technology's perception and pattern-matching abilities are being applied to improve progress in fields such as drug discovery and self-driving cars.

In this scenario, neighbours have been complaining that something smelly is coming from a nearby house. You've been called to the scene. This is what you'd hear if you were on one of the eight military and civilian bomb squad teams competing in the Robot Rodeo last week, an annual event hosted by Sandia National Laboratories in New Mexico.

Over 3.2 million pictures of animals - captured by hidden cameras - have been identified by Snapshot Serengeti volunteers and the data collected is being used to power the AI algorithm, using deep neural networks.

Google Translate has become the internet's go-to resource for short, quick translations from foreign languages. The service was first launched in April 2006, seeing off early competition from the likes of Babel Fish. It now boasts more than 500m users daily worldwide, offering 103 languages. But how exactly does it work? How does Google News actually work?

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?

The Rubik's Cube is a three-dimensional puzzle developed in 1974 by the Hungarian inventor Erno Rubik, the object being to align all squares of the same color on the same face of the cube. It became an international best-selling toy and sold over 350 million units. The puzzle has also attracted considerable interest from computer scientists and mathematicians. One question that has intrigued them is the smallest number of moves needed to solve it from any position. The answer, proved in 2014, turns out to be 26.

Artificial intelligence can now put itself in someone else's shoes. DeepMind has developed a neural network that taught itself to'imagine' a scene from different viewpoints, based on just a single image. Given a 2D picture of a scene – say, a room with a brick wall, and a brightly coloured sphere and cube on the floor – the neural network can generate a 3D view from a different vantage point, rendering the opposite sides of the objects and altering where shadows fall to maintain the same light source. The system, called the Generative Query Network (GQN), can tease out details from the static images to guess at spatial relationships, including the camera's position. "Imagine you're looking at Mt. Everest, and you move a metre – the mountain doesn't change size, which tells you something about its distance from you,"says Ali Eslami who led the project at Deepmind. "But if you look at a mug, it would change position.

MIT doctoral student Maria Bauza is exploring providing tactile feedback to robots. With the push of a button, months of hard work were about to be put to the test. Sixteen teams of engineers convened in a cavernous exhibit hall in Nagoya, Japan, for the 2017 Amazon Robotics Challenge. The robotic systems they built were tasked with removing items from bins and placing them into boxes. For MIT graduate student Maria Bauza, who served as task-planning lead for the MIT-Princeton Team, the moment was particularly nerve-wracking.

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.

Two legal challenges have been launched against police forces in south Wales and London over their use of automated facial recognition (AFR) technology on the grounds the surveillance is unregulated and violates privacy. The claims are backed by the human rights organisations Liberty and Big Brother Watch following complaints about biometric checks at the Notting Hill carnival, on Remembrance Sunday, at demonstrations and in high streets. Liberty is supporting Ed Bridges, a Cardiff resident, who has written to the chief constable of South Wales police alleging he was tracked at a peaceful anti-arms protest and while out shopping. Big Brother Watch is working with the Green party peer Jenny Jones who has written to the home secretary, Sajid Javid, and the Metropolitan police commissioner, Cressida Dick, urging them to halt deployment of the "dangerously authoritarian" technology. If the forces do not stop using AFR systems then legal action will follow in the high court, the letters said.