At Audi's most flexible plant, in Neckarsulm, Germany, the driver-side airbags are named after girls, while the steering wheels have boys' names. Other components are designated according to seasons or places: anything to make it easier for shop floor workers to remember when sorting and installing them. While a robot could read any of their 12-digit product identification codes in a microsecond, auto executives say the machines could not deal with the enormous complexity facing their human colleagues, who assemble six model lines and 21 vehicle derivatives at the plant. "Today it would be impossible to add all the sensors necessary to replace the human sense of touch," Audi production boss Hubert Waltl said. "People can reach into a box and without looking immediately recognize a larger part from a smaller one."

What could possibly go wrong? Elon Musk's AI set to try and learn the art of human conversation ...

The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention.

Nothing helps calibrate reality [more] than the honest perceptions of those who work closest to you.

Vikas Singhania Trade Smart Online Financial markets globally are changing not only in terms of price movements, informed participants, increased money flow and volatility but also structurally. While the others have always been a part of changing markets, it is the structural change that has the tendency of being disruptive in nature. The first sign of change was visible in Chicago that was the last bastion of open outcry trading system. This summer Chicago Mercantile Exchange Group closed most of its trading pits after 167 years. Algorithmic trading has fast replaced humans, accounting for nearly 70 per cent of trading volumes in leading exchanges globally.

Intel's secretive Knights Mill mega-chip will challenge GPUs for AI domination

It may not spring to mind as the first place you would turn to develop the art of conversation, but an AI firm backed by Elon Musk is hoping Reddit will help it's machine learn to converse. The OpenAI project is using a supercomputer known as a DGX-1 for its experiment, feeding popular Reddit threads to the AI for analysis, in the hope it will one day hold a conversation itself. However, the project follows a similar idea from Microsoft – which has to pull its learning chatbot after it began posting racist and offensive messages after just hours. OpenAI will feed popular Reddit threads to algorithms that have a probabilistic understanding of dialogue with the hopes it will one day hold a conversation itself. By feeding Reddit threads to DGX-1, it will hopefully read and learn a range of conversations faster than any other system has done before it, as conversations are filled with natural human language and commonly used slang.

"…[W]e are suspicious of rapid cognition. We live in a world that assumes that the quality of a decision is directly related to the time and effort that went into making it." According to folk wisdom, the more time, information, and effort you put into a decision, the better it gets. In other words, "More is better." If you are a doctor making a diagnosis, more medical tests are always better.

Detroit got its first toehold in Startup Nation on Tuesday, after Ford Motor Co. said it was buying SAIPS, an Israeli company that develops technologies that are key to self-driving vehicles. The acquisition was one of four deals the U.S. carmaker announced with the aim of having a high-volume, fully autonomous vehicle in commercial operation in 2021 in a ride-hailing or ride-sharing service. Ford said the investment/collaboration with the four startups is part of its strategy of enhancing its autonomous vehicle development, which includes more than doubling its staff at its Palo Alto, California, research and development center. Ford said SAIPS, a computer vision and machine-learning startup, would strengthen its expertise in artificial intelligence and enhanced computer vision. The company provided no financial details about its acquisition, but industry sources estimated it at tens of millions of dollars.

Although Chatbot UI (CUI) may seem like a new phenomenon, the technology has long been popular in countries like Japan and China. When Didi Dache integrated with WeChat's CUI for taxi service in 2014, the company quickly got over 700,000 bookings a day through WeChat alone. Fast forward to 2016: Silicon Valley has finally discovered CUI and has invested heavily in the sector, with hundreds of chatbots soon to be released into the market. One of the earliest steps in developing a chatbot is deciding how to give it a personality. Some companies take the Siri approach and choose not to give their chatbot a visual avatar, while Slack, for example, created the slackbot to make things a little more fun.