Nearly half a century has passed between the release of the films 2001: A Space Odyssey (1968) and Transcendence (2014), in which a quirky scientist's consciousness is uploaded into a computer. Despite being 50 years apart, their plots, however, are broadly similar. Science fiction stories continue to imagine the arrival of human-like machines that rebel against their creators and gain the upper hand in battle. In the field of artificial intelligence (AI) research, over the last 30 years, progress has been similarly slower than expected. While AI is increasingly part of our everyday lives - in our phones or cars - and computers process large amounts of data, they still lack human-level capacity to make deductions from the information they're given.

With a souped-up reproducing piano and some ingenious learning machines, AI maestro Gerhard Widmer is discovering how performers unlock the art in Mozart. A gray-blue dusk is settling over the Gothic cathedrals, palatial opera houses, and labyrinthine streets of Vienna's First District. Here in the Austrian capital, music is an almost elemental force. It's a place where very old and very new musical traditions collide and intermingle – the perfect setting for a computer scientist obsessed with examining the blips and fault lines, deviations and inventions, that transform music into something more than code and just slightly less than magic. This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. It's Friday evening, and most of his fellow teachers at the University of Vienna have already gone home, but associate professor Gerhard Widmer is bounding up the stairs of a peach-colored Baroque building and into the offices of the Austrian Research Institute for Artificial Intelligence. He waves hello to his team scientists – Simon Dixon, Emilios Cambouropoulos, and Werner Goebl – and makes for a computer monitor marked EUROPA, which is jacked into an electric piano. Widmer eagerly begins to trigger several audio files.

A renewed international effort is gearing up to design computers and software that smash language barriers and create a borderless global marketplace. A woman sits at a desk in Manhattan, talking to herself in French. The phrases she balances on each breath are musical to American ears. She has postcards of Montreal tacked up on the walls of her cubicle – pastel-painted houses in the snow – so as she sculpts the contours of each syllable, she can remind herself of the place where the sounds she's making are heard every day in the street. Her name is Guylaine Laperrière, and she came to New York City more than a decade ago to study musical theater. One day, a friend asked her if she wanted to make a little cash dubbing a French voice-over for a promotional short about insurance. She took the job, and was surprised how much she enjoyed bringing ideas from one language home into another. This article has been reproduced in a new format and may be missing content or contain faulty links.

ROBONAUT Not all NASA robots drive around poking at rocks. Robonaut is the same size and shape as a person in a space suit, so it can handle tasks typically performed by humans – its hands are even better articulated than an astronaut's gloved digits. The fact that it looks like Boba Fett? This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue.

This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. Seventeen of the world's most wired minds stake their names – and their cash – on the future. Pronouncements about the future come easy. Even when made with an air of authority, they're usually just cheap talk, rarely revisited. Only the tiny fraction that have proven correct tend to be remembered, when their authors want to take credit. The Long Bets Foundation, a new project masterminded by Well founder Stewart Brand and Wired editor at large Kevin Kelly, hopes to raise the quality of our collective foresight by incorporating money and accountability into the process of debate. If someone makes a grandiose claim, any skeptic can challenge it – "Would you bet on that?" – and the Long Bets Foundation will keep tabs on the wager, whether it takes five years or five decades to come to pass. If proven right, a predictor can relish the victory; if wrong, the challenger gets the glory. By preserving the terms of the wager in public view, Long Bets promises to be more than a service for confident prognosticators. Over time, it hopes to foster better understanding of how predictions in aggregate work out in reality – what kinds of truths are easiest (or hardest) to forecast, and what kinds of people are right (or wrong) most reliably. Following are the first-ever "long bets."

Sure, there are some morally and ethically questionable aspects of an unstoppable privatized security bot, but the armor and cyborgian capabilities are pretty freaking awesome. Why? Turns out we just don't have the battery power to operate a suit with that many moving parts for any length of time. Most iPhones barely last a full day on a charge, and a Tesla Model S can only make it about 300 miles before it needs to be plugged in--and that battery weighs more than 1,300 pounds (and is likely incapable of keep a human's organs running while being shot at). "That's one serious limitation that our technology is not approaching yet," says Charles Higgins, an electrical engineer and professor of neuroscience at the University of Arizona. "In order to do a real RoboCop like you see in the movie, you need to have a very compact power source that's going to power all those motors all day--it doesn't look like RoboCop has to plug in every hour."

The AI does not hate you, nor does it love you, but you are made of atoms it can use for something else

A few weeks into the making of Her, Spike Jonze's new flick about romance in the age of artificial intelligence, the director had something of a breakthrough. After poring over the work of Ray Kurzweil and other futurists trying to figure out how, exactly, his artificially intelligent female lead should operate, Jonze arrived at a critical insight: Her, he realized, isn't a movie about technology. With that, the film took shape. Sure, it takes place in the future, but what it's really concerned with are human relationships, as fragile and complicated as they've been from the start. Of course on another level Her is very much a movie about technology. One of the two main characters is, after all, a consciousness built entirely from code.

When we think about machine vision, we usually think about it in a human context. We build systems that can recognize faces in our photographs or count the number of cars in a traffic jam. Rare is the computer that's watching on its own terms. That got artist Ben Grosser wondering: Why not let a computer watch something for its own sake? What would that even look like?

In an age when technology companies routinely introduce new forms of everyday magic, one problem that remains seemingly unsolved is that of long-form transcription. Sure, voice dictation for documents has been conquered by Nuance's Dragon software. Our phones and smart home devices can understand fairly complex commands, thanks to self-teaching recurrent neural nets and other 21st century wonders. However, the task of providing accurate transcriptions of long blocks of actual human conversation remains beyond the abilities of even today's most advanced software. When solved on a broad scale, it is a problem that might unlock vast archives of oral histories, make podcasts easier to consume for speed-readers (tl;dl), and be a world-changing boon for journalists everywhere, liberating precious hours of sweet life.