Artificial intelligence is the next big thing in the world of computing, and it is already there. Google's Pixel smartphones, which come with an inbuilt Google Assistant that can get you anything from the daily dose of news to meditation tips, has already started selling in India. Siri is more intelligent than before; it lets you chat her up to find a good place to eat nearby and even draft an email for you. But the biggest use of artificial intelligence might be in bringing down the bar to access for millions of people who find all the text and foreign languages on smartphones hard to comprehend. That is exactly what companies like Karbonn, who think more mass than niche, are working on.

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Move over desktop: Mobile is the future of online purchases and commerce, thanks to its ability to connect with location-based and personalized data. Forrester's new report "Predictions 2017: Mobile is the Face of Digital," scheduled to be publicly released Tuesday, explains that mobile has become the new pathway for consumers find brands -- and it is moving past the traditional social media app. Advertisers will increasingly use mobile to connect next year using chatbots, other artificial intelligence-enabled platforms like Apple's Siri or Amazon's Alexa and messaging apps, the report said. The company previously said that people spend more than two hours a day on mobile, and that by 2019 the majority of our billion websites will be on mobile. "The magic of mobile is the immediacy," said Julie Ask, principal analyst at Forrester and co-author of the report.

Arvid Tchivzhel, Director of Product Development, Mather Economics, Arvid Tchivzhel, a director with Mather Economics oversees the delivery and operations for all Mather Economics consulting engagements, along wit... The old adage is as true as ever in the world of open source technology: "Those who do not learn history are doomed to repeat it." Numerous surveys, articles, listicles and case studies address best practices for companies wishing to implement a Big Data project and make a return on their investment. Machine learning is the new buzzword to take hold among executives (and in the marketing materials of enterprise consultants). Before plunging into the world of machine learning, firms should pause and learn from the mistakes made in the implementation of Big Data projects over the last five years.

MIT's Nightmare Machine puts Halloween scares in hands of AI

Honda Motor Co. will spearhead its artificial intelligence efforts out of a new lab in Tokyo so that researchers can work closely with its engineers to commercialize the technology. Honda, based in Tokyo, will start the R&D center next year and combine existing AI teams in Silicon Valley, Europe and Japan at the downtown location, according to Yoshiyuki Matsumoto, president of the automaker's largely independent research arm. In choosing Tokyo over Silicon Valley, the carmaker is betting closer interaction between its scientists and developers will lead to AI-enabled products consumers want, he said in an interview. Advances in artificial intelligence are sprouting like "bamboo shoots after rain," so it's time to find commercial uses for the technology by marrying research with Japan's traditional strength in hardware, Matsumoto said. "We won't make much difference if we did the same things as everyone else in Silicon Valley. And not everyone has succeeded there."

MIT's Nightmare Machine puts Halloween scares in hands of AI

"In real-world applications, sometimes people want to know why the model makes the predictions it does," said graduate student Tao Lei. "One major reason that doctors don't trust machine-learning methods is that there's no evidence." "You may not want to just verify that the model is making the prediction in the right way; you might also want to exert some influence in terms of the types of predictions that it should make," commented Tommi Jaakkola, an MIT professor of electrical engineering and computer science. The researchers address neural nets trained on textual data. To enable interpretation of a neural net's decisions, the group divide the net into two modules.

The idea of artificial intelligence (AI) -- autonomous computers that can learn independently -- makes some people extremely uneasy, regardless of what the computers in question might be doing. Those individuals probably wouldn't find it reassuring to hear that a group of researchers is deliberately training computers to get better at scaring people witless. The project, appropriately enough, is named "Nightmare Machine." Digital innovators in the U.S. and Australia partnered to create an algorithm that would enable a computer to understand what makes certain images frightening, and then use that data to transform any photo, no matter how harmless-looking, into the stuff of nightmares. Images created by Nightmare Machine are unsettling, to say the least.

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