Recently, BMW mentioned that it would introduce an autonomous car by 2021, called the iNext. The automaker hasn't released much detail about the vehicle, but it will most likely resemble the similar-sounding Vision Next 100 concept vehicle, which the company showed off back in March. At BMW's annual shareholder meeting this month, the company's CEO, Harald Krueger, said, "Our goal is already clearly defined -- to be number one in autonomous driving." But BMW will find plenty of driverless-car competition among its fellow luxury automakers, most specifically from Mercedes-Benz parent company Daimler. Daimler is currently a leader in driverless technology among automakers, and it's likely Krueger's mention of autonomous tech is an effort to reassure investors the German automaker isn't falling behind one of its biggest rivals. But which carmaker is leading in driverless tech?

In 2010, IFTF's Ten-Year Forecast suggested that the future is a high-resolution game: Never before has humanity been able to encounter the future in such detail, to measure the forces of change at such vast scales, and to fill in the details with such fine grain. As we play this game, we find ourselves in ever more layered and nuanced futures that often look distinctly different across geographies, across cultures, and even across the various identities each of us claims. More than a fragmented marketplace or a contentious body politic, this future looks like a massively branching game environment where you can win without ever discovering half of the possible pathways--but you can lose by mistaking a clear line of sight for the whole story. As we try to grasp the future of blockchain and other distributed computing technologies, we have to start here, with this high-resolution gamescape where there is no single blockchain future. Rather, we face an ecosystem of futures as complex as the global superorganism that we are actually becoming.

Sometimes, really brilliant folks with a reputation for being brilliant start to comment on subjects outside their area of expertise, as if their level of genius so transcends the intelligence of the unwashed masses that they can be called on as an authority in literally any subject. Stephen Hawking has arguably been guilty of this before, and has faced criticism for his recent pontifications on the dangers of artificial intelligence in particular. But on Tuesday, Hawking admitted to being utterly stumped by something -- or, rather, someone: Donald Trump. ITV's "Good Morning Britain" cheekily asked whether the physics genius could explain the American billionaire's rise to presidential candidacy. "He's a demagogue who seems to appeal to the lowest common denominator." Hawking, who has lived with amyotrophic lateral sclerosis (ALS) for more than half a century, uses a computer controlled by tiny movements of his cheek muscles to type out communications.

Inside the glistening red cave of the patient's abdomen, surgeon Michael Stifelman carefully guides two robotic arms to tie knots in a piece of thread. He manipulates a third arm to drive a suturing needle through the fleshy mass of the patient's kidney, stitching together the hole where a tumor used to be. The final arm holds the endoscope that streams visuals to Stifelman's display screens. Each arm enters the body through a tiny incision about 5 millimeters wide. To watch this tricky procedure is to marvel at what can be achieved when robot and human work in tandem. Stifelman, who has done several thousand robot-assisted surgeries as director of NYU Langone's Robotic Surgery Center, controls the robotic arms from a console.

A few weeks ago, an anonymous website arrived with a countdown clock, one set to hit zero on May 31. The domain, Prophets of Rage, is named for a Public Enemy song, and arrived with a red-and-black militaristic logo. Prophets of Rage also started posting oblique Instagram photos and embeds of Public Enemy and Cypress Hill tracks. It did all this while referencing a hashtag: #takethepowerback. This wasn't a political movement or an armed insurrection.

Imagine owning an Amazon Echo, only it was in robot form and could perform tasks like entertaining kids or keeping tabs on seniors. On Tuesday, tech company unveiled the Zenbo home robot, a 599 tech companion capable of roaming your home and assisting users with requests from sharing recipes by voice to controlling the lights or air conditioning. The Zenbo was revealed during the tech conference Computex in Taiwan. "Our ambition is to enable robotic computing for every household," said Asus Chairman Jonney Shih in a statement. The robot's face doubles as a touchscreen users can tap or swipe for a variety of tasks, but it can also respond to voice commands. It also plays music, respond to questions, take pictures or make video calls and even tell stories to kids.

Stock photo giant Shutterstock is boosting its artificial intelligence (AI) credentials today with the launch of a new reverse image search feature within its iOS app. The New York-based company offers more than 80 million images for bloggers and media outlets, but keyword searches aren't always the most effective way to find images relevant to a story. If you want to search for photos that are similar to ones you already have in your possession, or if you want to find alternative photos based on the shapes, mood, color scheme, and general mise en scène around you, reverse image search comes into play. You can search Shutterstock by using the camera on your iPhone or the photos on your camera roll to find similar images. The launch comes three months after Shutterstock first introduced the feature through its desktop version, though extending it to smartphones does feel like a natural move, given that smartphones are cameras in their own right. "When we unveiled Reverse Image Search this past spring, we knew that it was a perfect fit for our mobile application -- it's arguably one of the best use cases for computer vision technology, in general," said Shutterstock CEO and founder Jon Oringer.

AI is one of those technologies whose promise is resurrected periodically, but only slowly advances into the real world. I remember the dog-and-pony AI shows at IBM, MIT, Carnie-Melon, Thinking Machines, and the like in the mid-1980s, as well as the technohippie proponents like Jaron Lanier who often graced the covers of the era's gee-whiz magazine like "Omni." AI is an area where much of the science is well established, but the implementation is still quite immature. It's not that the emperor has no clothes -- rather, the emperor is only now wearing underwear. There's a lot more dressing to be done.

But a new super-dexterous robot hand can "learn" how to perfect new abilities over time -- without any help from its three human overlords at the University of Washington. The trio of researchers presented their handiwork, called the Adroit manipulation system, on Tuesday at the International Conference on Robotics and Automation in Stockholm. The Adroit system gets the world one step closer to the Jetsons' housekeeper robot Rosie: hardware that performs better than human bodies, yet is controlled by a software "brain" that learns like a human mind. The researchers say their creation has potentially huge implications for the robotics field, and for any industry that requires a variety of complex tasks -- from space exploration to healthcare to automated butlers. Manipulating robot hands to perform fine-motor tasks like catching a stick, rotating a tube or rolling a block "is one of the biggest problems in robotics," lead researcher Vikash Kumar told CNNMoney.

Artificial intelligence (AI) has been implemented in multiple industries, from stock trading to hospitals, and Google has singled it out as the next big thing. As Uschi Schreiber, Chair of the Global Accounts Committee at EY, wrote earlier this year: "Leaders in every industry are responding to shifts that would have seemed unimaginable even a few years ago. "Artificial intelligence (AI) and robotics are fundamentally reinventing the workforce." The finance sector, given its heavy reliance on mass amounts of numbers and data, is a prime candidate for the automation offered by intelligent learning systems. But while this might mean great things for efficiency and digital transformation, many have raised concerns about robots taking the place of human employees. The driving motivations behind the installation of AI in business processes appear to be the greater speed, accuracy and volume capability of computers when compared to their existing human counterparts. Many businesses are already using robotic process automation systems to crunch numbers and sift data on a daily basis. For example, Kensho is an intelligent computer system widely used by stock traders and investors to automatically analyse portfolio performance and predict market changes. The software is described as'the world's first computational knowledge engine for the financial industry'. It claims to address Wall Street's greatest challenge – automating and improving on previously human-intensive knowledge work to keep up with the split-second changeability of stock. Kensho's founder, Daniel Nadler, told the New York Times Magazine: ''People always tell me, 'I used to spend two out of five days a week doing this sort of thing,' or'I used to have a guy whose job it was to do nothing other than this one thing'.'' Even the breaking down and translating of numerical data into colloquial terms no longer requires the input of a human operator, thanks to systems that learn with use to mimic personable patterns. UK-based Arria has developed natural language generation software (NLG) that is being used across a wide range of industries to humanise and simplify the analysis of data heavy reports. Arria's Chief Technology Officer Robert Dale, said: "By emulating human behaviour in software, you get technology that can carry out tasks that are more than just straightforward number crunching, with the machine exhibiting real intelligence.