Local Motors officially unveiled its self-driving shuttle Thursday and said it will begin giving free rides to the public in Maryland this summer. The electric vehicle, which seats 12, will drive slowly on public roads in National Harbor, Md., operating at speeds between 3 and 8 mph, according to Local Motors chief executive Jay Rogers. He characterized Olli as a "friendly neighborhood robot" that isn't capable of traveling on highways. "A full win for Olli, when we can hook up the victory flag and say we're done here, is when a city says no more cars on our streets," said Rogers, citing concerns about distracted drivers creating unsafe situations for pedestrians and cyclists as a motivation for creating Olli. Local Motors, which is best known for its 3-D printed vehicles, has produced two prototypes of Olli so far.

Google announced in a blog post on Thursday that it has set up a new AI research group in Europe to focus on machine learning (ML). Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Google Research, Europe -- as the group is known -- is based out of Google's office in Zurich, Switzerland, which is home to Google's largest engineering office outside the US. Google said the group, which is expected to grow to over 100 people in the coming years, will focus on three key areas: machine intelligence, natural language processing and understanding, and machine perception. Companies like Amazon, Facebook, and Microsoft are all investing heavily in these areas as they look to make their platforms and services more intelligent.

This archive file was compiled from an interview conducted at the Googleplex in Mountain View, California, 2013. As late as the 1980s and the 1990s, the common person seeking stored knowledge would likely be faced with using an 18th century technology - the library index card catalogue - in order to find something on the topic he or she was looking for. Fifteen years later, most people would be able to search, at any time and any place, a collection of information that dwarfed that of any library. And unlike the experience with a library card catalogue, this new technology rarely left the user empty-handed. Information retrieval had been a core technology of humanity since written language -- but as an actual area of research it was so niche that before the 1950s, nobody had bothered to give the field a name.

Google has made no secret of its AI ambitions, and on Thursday it announced the next step in its bold plans to realize them: a brand-new research group in Europe focused squarely on machine learning. Based in Google Research offices in Zurich, Switzerland, the new group will focus on three key areas of artificial intelligence: machine intelligence, machine perception, and natural language processing and understanding, according to a blog post by Emmanuel Mogenet, head of Google Research for Europe. It will research ways to improve machine-learning infrastructure and enable the technology for practical use, for instance. Researchers will also work closely with linguists to advance natural language understanding, Mogenet said. Zurich, meanwhile, is home to Google's largest engineering office outside the U.S. Researchers there developed the engine that powers Knowledge Graph as well as the conversation engine that powers the Google Assistant in its Allo messaging app. Google's presence in Europe hasn't been entirely smooth, however: It's facing ongoing scrutiny over antitrust concerns and tax issues.

You might offer your employees gym membership. You may provide them with fresh fruit and free coffee. No doubt you give them opportunities to learn, chances to feel challenged, work that enthuses and excites them. But sometimes, a seemingly perfect package still can't satisfy. Today, we face a global crisis; one rarely discussed, but widely felt. Approximately 450 million people worldwide have a mental health problem.

IBM has teamed up with Local Motors, a Phoenix-based automotive manufacturer that made the first 3D-printed car, to create a self-driving electric bus. Named "Olli," the bus has room for 12 people and uses IBM Watson's cloud-based cognitive computing system to provide information to passengers. In addition to automatically driving you where you want to go using Phoenix Wings autonomous driving technology, Olli can respond to questions and provide information, similar to Amazon's Echo home assistant. The bus debuts today in the Washington D.C. area for the public to use during select times over the next several months, and the IBM-Local Motors team hopes to introduce Olli to the Miami and Las Vegas areas by the end of the year. By using Watson's speech to text, natural language classifier, entity extraction, and text to speech APIs, the bus can provide several services beyond taking you to your destination.

What makes Olli, the car that's now rolling through the streets of National Harbor, Maryland, important isn't that it drives itself, that it's electric, or even that Local Motors made it from 3-D printed parts. What sets Olli apart is its gift of gab. Upstart automaker Local Motors and IBM teamed up to create the autonomous van-like shuttle, which launches today, carries twelve passengers, and uses the tech stalwart's Watson supercomputer to chat with passengers. That may seem a step down from fighting cybercrime, predicting the weather, and whooping human butts at Jeopardy!, but it's a clever use of Watson's cognitive speech capabilities to solve one of the more devilish problems blocking our path to a world of autonomous vehicles: How to make people trust them. As they ride around Local Motors' facility a few miles down the Potomac from Washington, DC, passengers can hit a button and ask Olli questions.

Artificial intelligence, which has been around since the 1950s, has seen ebbs and flows in popularity over the last 60 years. But today, with the recent explosion of big data, high-powered parallel processing, and advanced neural algorithms, we are seeing a renaissance in AI--and companies from Amazon to Facebook to Google are scrambling to take the lead. According to AI expert Roman Yampolskiy, 2016 is the year of "AI on steroids." How the'PayPal Mafia' redefined success in Silicon Valley A decade ago, the PayPal Mafia played a major role in revitalizing the tech industry in Silicon Valley. The story behind this group of leaders proves that their success is more than just luck.

"Warcraft," the critically panned video game-inspired film from Legendary Entertainment, made more than six times as much money in China as it did in the U.S. during its opening weekend, and it had observers including Jackie Chan saying it could be the harbinger of a new age in blockbuster filmmaking. That's undoubtedly a historic split for a Hollywood film -- although it's not unusual for a movie to make more in China than at home -- and certainly something that could happen more as China's rapidly growing box office catches up with the U.S. Rather, "Warcraft" is just a movie with several unique factors that gave it a much bigger potential audience in China than anywhere else. The world is big, interests are regional, and Chinese companies have certain competitive (or anticompetitive) advantages that Hollywood studios don't, like a restriction on foreign competition and the ability to own theater chains. As a result of such factors, "Warcraft" blew the doors down in China, but it didn't really blaze a trail that too many other movies could realistically follow. China is a nearly 8 billion -- and growing -- movie market with only 34 slots for Western films, so naturally Hollywood is going to produce its megabudget blockbusters with that in mind, taking steps not to offend the Chinese state censors that have to approve every imported film.

Ask any soccer fan who will win the Euro 2016 championship and every one of them will have an opinion, fueled by a combination of patriotism, passion and hope. It's safe to say none of them will offer an opinion based on the results of more than 36,000 soccer matches held during the past 146 years and an analysis of 94 billion outcomes. That's what researcher Michael Feindt, a particle physicist who worked at the European Organization for Nuclear Research (CERN) for six years, has done. At CERN, Feindt created an algorithm to predict collisons of particles inside the Large Hadron Collider. Now he's CEO of Blue Yonder, a startup looking to commercialize the technology in retail, logistics, manufacturing and transportation, a process he describes as finding the "the possibilities of probable futures."