In an ordinary conference room in this city of start-ups, a group of engineers sat down to order pizza in an entirely new way. "Get me a pizza from Pizz'a Chicago near my office," one of the engineers said into his smartphone. It was their first real test of Viv, the artificial-intelligence technology that the team had been quietly building for more than a year. Everyone was a little nervous. Then, a text from Viv piped up: "Would you like toppings with that?"

Ever since the 1980s, researchers have been working on the development of a quantum computer that would be exponentially more powerful than any of the digital computers that exist today. And now Google, in collaboration with NASA and the Universities Space Research Association (USRA), says it has a quantum computer -- the D-Wave 2X -- that actually works. Google claims the D-Wave 2X is 100 million times faster than any of today's machines. As a result, this quantum computer could theoretically complete calculations within seconds to a problem that might take a digital computer 10,000 years to calculate. That's particularly important, given the difficult tasks that today's computers are called upon to complete and the staggering amount of data they are called upon to process.

Machines may yet take over the world, but first they must learn to recognize your dog. To hear Google executives tell it at their annual developer conference this week, the technology industry is on the cusp of an artificial intelligence, or AI, revolution. Computers, without guidance, will be able to spot disease, engage humans in conversation and creatively outsmart world champions in competition. Such breakthroughs in machine learning have been the stuff of science fiction since Stanley Kubrick's 1968 film 2001: A Space Odyssey. "I'm incredibly excited about the progress we're making," CEO Sundar Pichai told a crowd of 7,000 developers at Google I/O from an outdoor concert stage.

People who rely on satnav could be at risk of losing their ability to navigate, an expert has warned. Writing in the journal Nature, former president of the Royal Institute of Navigation Roger McKinlay argues that our reliance on GPS technology is misplaced and could be eroding our innate way-finding abilities. "If we do not cherish them, our natural navigation abilities will deteriorate as we rely ever more on smart devices," he wrote. McKinlay believes huge investment will be needed before navigation systems will be good enough to allow technologies such as autonomous vehicles to take off. In the meantime, he argues, we need better research into systems for navigation while children should be encouraged to learn how to find their way around by more traditional means.

The Ministry of Defence is organising its first-ever "Robo-Wars" exercise this autumn, using drones, seacraft and a host of other innovations as part of the growing trend towards reducing the role of humans in combat. The large-scale event off the west coast of Scotland will form part of the regular UK-led Nato Joint Warriors exercise. The navy, on its website, is billing the robotic part as "Unmanned Warrior 2016", and says: "Recognising a commitment to innovation, the Royal Navy will host a large-scale demonstration in a tactically representative environment of maritime autonomous systems in the autumn of 2016." More than 80 countries around the world, including the US and China, have stepped up research and development of "killer robots" and other non-human forms of warfare. Although large-scale civilian casualties from robotic warfare – mainly from drones – are already a reality, military personnel, analysts and academics have predicted that combat would one day be conducted between armies of robots and unmanned vehicles.

Despite advances in forensic techniques, criminal investigations still rely on age-old tools such as eyewitness testimony, which can be biased and unreliable. But what if we could take advantage of other human abilities, such as sense of smell or a talent for facial recognition? Researchers are exploring that possibility and other crime-fighting techniques that rely less on human judgment and more on big data crunching such as an algorithm that predicts an offender's risk of committing another crime. These approaches need to be validated before we put them to use, but research suggests they could be a boon to the criminal justice system. Imagine witnessing a crime and being called into a police station where a detective presents you with an array of human scents.

NOW your phone knows you better than ever. The latest version of Apple's mobile operating system learns what your voice sounds like, and can identify you when you speak to Siri, ignoring other voices that try to butt in. Siri, the intelligent personal assistant, is not the only one who knows your voice. As learning software improves, voice-identification systems have started to creep into everyday life, from smartphones to police stations to bank call centres. More are probably on the way.

IN THE near future, you may have to share the road with a robot. Or perhaps we should say that a robot will have to share the road with you. At the University of California, Berkeley, engineers are preparing autonomous cars to predict what we impulsive, unreliable humans might do next. A team led by Katherine Driggs-Campbell has developed an algorithm that can guess with up to 92 per cent accuracy whether a human driver will make a lane change. She is due to present the work next month at the Intelligent Transportation Systems conference in Las Palmas de Gran Canaria, Spain.

Machine minds are often described as black boxes, their decision-making processes all but inscrutable. But in the case of machine intelligence, researchers are cracking that black box open and peering inside. What they find is that humans and machines don't pay attention to the same things when they look at pictures – not at all. Researchers at Facebook and Virginia Tech in Blacksburg got humans and machines to look at pictures and answer simple questions – a task that neural-network-based artificial intelligence can handle. They wanted to map human and AI attention, in order to shed a little light on the differences between us and them.

Google DeepMind took a leap forward last year when its artificial intelligence agent mastered 49 Atari 2600 games. The learning system, or "deep Q-network" (DQN), that DeepMind designed achieved this mastery through general experience, rather than specific programming for each game. This milestone is just one step along a grander path toward the general-purpose "smart machine": an AI that can master any task with minimal input. DeepMind's work in this field is groundbreaking, and it's helping advance the field in ways you might not expect. Wojciech Jaśkowski is an assistant professor at the Institute of Computing Science (ICS) at Poznan University of Technology, Poland.