Kawasaki Heavy Industries, which manufacturers Kawasaki motorcycles, heavy equipment, aerospace and defense machines, has reported that it will begin developing motorcycles that can speak directly to the rider through the use of ICT (Information and Communications Technology), which includes AI (Artificial Intelligence). Using "Emotion Generation Engine" and "Natural Language Dialogue System," the motorcycle will be able to directly communicate with the rider via voice. This will allow the motorcycle to understand the owner's riding style, and update its suspension and engine settings to accommodate the owner's riding style. The system, currently under development by cocoro SB Corp., will allow the motorcycle to communicate with the rider by recognizing emotion in the sound of the rider's voice. "Accessing Kawasaki's bank of analytical chassis and performance data, the system will be able to offer the rider pertinent hints for enhanced riding enjoyment, or relay information as the situation dictates. Through advanced electronic management technology, having the system update machine settings based on the rider's experience, skill and riding style will also be possible," Kawasaki says.

There are few subjects in computing as fascinating, or intimidating, as machine learning. Let's face it -- you can't master machine learning in a weekend, and at the very least it requires a good grasp of the underlying mathematical principles. That said, if you have the math chops, you'll want to augment your use of machine learning frameworks (there are plenty to pick from) with a good understanding of the theory behind them. Here are five high-quality, free-to-read texts that provide introductions to and explanations of machine learning's ins and outs. Some have code examples, but most focus on formulas and theory; in principle, they can be applied to any number of languages, frameworks, or problems.

Stanford has undertaken an important effort: envisioning the implications of artificial intelligence over a 100-year span, to "anticipate how the effects of artificial intelligence will ripple through every aspect of how people work, live, and play." But there is a problem, potentially fundamental enough that the team may want to revisit its first report or adjust its approach as it goes forward. This is the report's relatively weak coverage of the urban, human security implications of AI. According to the purpose statement, this first study focuses on the implications of AI in 2030 in the "typical North American city." I suppose the thin treatment of security may derive from the huge assumption that North American cities will remain peaceful and secure, and thus AI and intelligent machines won't carry significant human security implications.

US lawmakers mull long and short-term CRs, and'minibus' appropriations packages. Out of the shadows, the SCO now needs to justify its long-term existence to a new president. Defense dollars are the big issue as the'Big Four' lawmakers met to negotiate the 2017 defense poli… In a recent visit, Lockheed Martin's proposed move of the F-16 production line to India was a subjec… Directed energy may be ready in the future, but Kendall is tempering excitement. In a recent visit, Lockheed Martin's proposed move of the F-16 production line to India was a subjec… The next administration will grapple with the F-35's move to full-rate production and the first set… Is MEADS Back in Running for Poland's Missile Defense Competition? The United States is set to approve the sale of Mk-48 heavyweight torpedoes for Taiwan.

Can you imagine life without your smartphone? The last time I forgot mine at home I felt a bit lost, disconnected and just plain naked. Like I'd left an arm or a leg at home. Yet the fact that 79% of smartphone users are never more than an arm's reach from their phones, I know I'm not alone. So when I started to hear rumblings that smartphones could be on their way out in the next few years, I almost choked on my coffee.

Just like Keras, it works with either Theano or TensorFlow, which means that you can train your algorithm efficiently either on CPU or GPU. This means that evaluating and playing around with different algorithms is easy. Of course you can extend keras-rl according to your own needs. You can use built-in Keras callbacks and metrics or define your own. Even more so, it is easy to implement your own environments and even algorithms by simply extending some simple abstract classes.

"I'm sorry Dave, I'm afraid I can't do that." If you've ever seen Stanley Kubrick's 1968 sci-fi film, 2001: A Space Odyssey, you might think twice about putting your faith in machines with artificial intelligence. Kawasaki Heavy Industries, Ltd. (KHI), however, is betting that the reality of artificial intelligence--or AI--will be not only benign, but a boon to the motorcycling experience. Kawasaki says it plans to develop "next-generation motorcycles that can grow along with the rider" using a combination of ICT (Information and Communications Technology) and AI (Artificial Intelligence). These motorcycles of the future will use something called the Emotion Generation Engine and Natural Language Dialogue System, said to be "a form of artificial intelligence that enables man and machine to communicate with technology capable of recognizing emotion by the sound of the speaker's voice," using a platform being developed by cocoro SB Corp., a member of the SoftBank Group.

Dmitry Malioutov can't say much about what he built. As a research scientist at IBM, Malioutov spends part of his time building machine learning systems that solve difficult problems faced by IBM's corporate clients. One such program was meant for a large insurance corporation. It was a challenging assignment, requiring a sophisticated algorithm. When it came time to describe the results to his client, though, there was a wrinkle. "We couldn't explain the model to them because they didn't have the training in machine learning." In fact, it may not have helped even if they were machine learning experts. That's because the model was an artificial neural network, a program that takes in a given type of data--in this case, the insurance company's customer records--and finds patterns in them. These networks have been in practical use for over half a century, but lately they've seen a resurgence, powering breakthroughs in everything from speech recognition and language translation to Go-playing robots and self-driving cars.

Artificial intelligence might be on its way Photo credit: David Molina Evan Roberts and David MolinaSeptember 10, 2016Filed under Opinion # Hang on for a minute...we're trying to find some more stories you might like. Close # Email This Story Send Email Cancel Siri was first introduced in 2011 on the iPhone 4S. When it was first introduced it was fun to play with and receive cute responses from, but it was not too useful. Since then, Siri and its competitors have become increasingly more use... U.S. – Google Inc. (NASDAQ: inGOOGL) is working with a third-party company called DeepMind to enhance their AI personal assistant.