Sitting in his office overlooking downtown Bellevue, Washington, Microsoft's Fil Alleva is talking about the long and sometimes difficult road he and other speech recognition experts have taken from the early work of the 1970s to the situation he is in today, where he can turn to his computer and say, "Cortana, I want a pizza" and get results. The conversation quickly drifts deeply into the technology that makes something like that possible, and then Alleva pauses. "What we all had in the back of our minds, whether we say it or not, was C-3PO," he admits with a grin. The personable "Star Wars" character who can understand and speak millions of languages may not have been the only inspiration for the world's leading researchers – some also will say that the universal translator that was featured prominently in "Star Trek" spurred their dreams along. But regardless of whether they were "Star Wars" fans or "Star Trek" loyalists, one thing is clear: The quest to create a computer that can understand spoken language as well as a person was for years so fanciful that the only thing to compare it to was science fiction.

The first elephant to don a prosthetic limb is challenging surgeons to create bigger, better legs. Mosha lost her right foreleg below the knee in a landmine explosion when she was seven months old. Therdchai Jivacate, a surgeon who designs prosthetic legs for humans and other animals, met her in 2007 at the Friends of the Asian Elephant Foundation in Thailand. "When I saw Mosha, I noticed that she had to keep raising her trunk into the air in order to walk properly," Jivacate told Motherboard. He built a prosthetic leg for Mosha that relieved the strain she had been putting on her limbs and spine.

Industrial companies are confronted with several new trends that will fundamentally change production and logistics processes. For example, the term "Industry 4.0," which was coined in Germany, stands for the digital networking of people, objects, and systems to create integrated production processes. In international jargon, it is referred to as the Industrial Internet of Things (IIoT). All technologies, systems, and components that are involved in the industrial value creation process are connected to each other as well as to company networks and the internet. Smart factory is another trend that forms a part of the IIoT development.

Microsoft seems to be on an acquiring spree as the company on Friday said that it had acquired messaging app developer Wand Labs. "This acquisition accelerates our vision and strategy for'Conversation as a Platform', which Satya Nadella introduced at our Build 2016 conference in March," David Ku, corporate vice president at Information platform group divison at Mircosoft, said. Satya Nadella, CEO of Microsoft, who was on a India visit recently, had said his company was trying to teach computers the human language to make computing faster by using artificial intelligence assistants such as Cortana, a programme that runs on most Windows devices and gets tasks done by speech recognition. "We are going to bring in bots which will result in democratisation for developers who would look at reinventing apps for speech recognition via a virtual assistant that would make human lives easier," he had added. Ku further justified the acquisition and said: "Wand Labs' technology and talent will strengthen our position in the emerging era of conversational intelligence, where we bring together the power of human language with advanced machine intelligence -- connecting people to knowledge, information, services and other people in more relevant and natural ways. It builds on and extends the power of the Bing, Microsoft Azure, Office 365 and Windows platforms to empower developers everywhere."

Multi-label classification has received considerable interest in recent years. Multi-label classifiers have to address many problems including: handling large-scale datasets with many instances and a large set of labels, compensating missing label assignments in the training set, considering correlations between labels, as well as exploiting unlabeled data to improve prediction performance. To tackle datasets with a large set of labels, embedding-based methods have been proposed which seek to represent the label assignments in a low-dimensional space. Many state-of-the-art embedding-based methods use a linear dimensionality reduction to represent the label assignments in a low-dimensional space. However, by doing so, these methods actually neglect the tail labels - labels that are infrequently assigned to instances. We propose an embedding-based method that non-linearly embeds the label vectors using an stochastic approach, thereby predicting the tail labels more accurately. Moreover, the proposed method have excellent mechanisms for handling missing labels, dealing with large-scale datasets, as well as exploiting unlabeled data. With the best of our knowledge, our proposed method is the first multi-label classifier that simultaneously addresses all of the mentioned challenges. Experiments on real-world datasets show that our method outperforms stateof-the-art multi-label classifiers by a large margin, in terms of prediction performance, as well as training time.

Video Friday is your weekly selection of awesome robotics videos, collected by your multilayer Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Also I want that thing that will fire birdies at me. The first robot to autonomously and intentionally break Asimov's first law, which states: A robot may not injure a human being or, through inaction, allow a human being to come to harm.

A 25-year-old Erik Spoelstra used to sit in a storage room in the old Miami Arena, evaluating hours of game film to review player performance as an entry-level NBA video coordinator. Eventually, he climbed out of the audio visual muck to become head coach of the NBA's Miami Heat, where he would go on to win two championships. It's a classic story of rags to riches--rising from junior video coordinator to head coach in about 13 years--and it may now be unlikely to ever happen again, as computers take over the position that gave Spoelstra his start. "If an AI were fed videos of a huge number of past NBA games, and were smart enough to understand the events occurring in the games, then it could do a better job at making tactical basketball decisions like choosing starting lineups," said Ben Goertzel, a prominent futurist and lead researcher in the OpenCog AI lab at Hong Kong's Polytechnic University. "As AIs with robust video understanding become widespread, I'd expect that we could see AI sports assistants start to play a serious role," he said.

Kaname Hayashi is known as the "Father of Pepper." Hayashi is the "father of Pepper," the charming humanoid robot from Japanese carrier SoftBank Mobile and French company Aldebaran Robotics. Pepper, with its circular doe eyes and welcoming smile, is billed as a robot that can read your emotions. It's available for sale and has even enrolled in school. Like any proud parent whose kids leave home, Hayashi had a void to fill.

Anirudh Koul's grandfather was slowly losing his ability to see. By 2014, he was having a hard time recognizing Koul's face in their weekly Skype calls bridging the vast distance between the Silicon Valley, where Koul is a data scientist at Microsoft, and the elderly man's home in New Delhi. So Koul started reading up on the challenges of vision loss and thinking about how the recent advances in deep learning, a potential-packed area of machine learning, could help give people a new way to recognize what's around them without actually seeing it. That was the modest beginning of Seeing AI. Two years later, Microsoft CEO Satya Nadella introduced the budding technology to thundering applause at this year's Build conference.

ZUMATA, a Singapore-based hotel distribution and technology company, along with DHISCO, the world's leading hospitality distribution company headquartered in Dallas, Texas, today announced a reciprocal agreement aimed to increase each other's hotel inventory while accelerating their mutual geographic expansion of distribution. ZUMATA, through its extensive network of wholesale partners and channel managers will supplement DHISCO's inventory by providing over 500,000 instantly bookable hotel properties. For ZUMATA, DHISCO will facilitate distribution of this hotel inventory to its large customer base largely based in North America and other Western markets. "DHISCO has been an industry powerhouse for years, and yet their management is keenly focused on innovation," said ZUMATA CEO Josh Ziegler. "This partnership underscores their commitment to staying at ahead of their competition by embracing the latest technological advancements. For us, this partnership represents a significant opportunity for our partners to gain access to DHISCO's amazing distribution. Complementing inventory and distribution, our artificial intelligence, or AI, powered technology will add exciting new capabilities that can increase customer satisfaction while increasing performance and conversions for all of us."