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67% of consumers worldwide used a chatbot for customer support in the past year (Source: Business Insider). In 2017, 35.6 million Americans will use a voice-activated assistant device at least once a month.

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The chatbot is friendly and can offer Sara immediate assistance. It’s already the night before Sara’s trip to Morocco! Machine: to find out what happens when we get to the planet earth. Google's paper shows they can also drive chatbots, and perhaps move us closer to a world where machines can converse like humans."With papers like this, people always give the most impressive interactions," says Chris Nicholson, founder of the neural networking startup Skymind. And this represents a significant front in the industry."Google's chatbot draws on research from across the larger AI community, including work from University of Montreal professor Yoshua Bengio and researchers at Facebook and Microsoft. At these internet giants, neural nets are already working to recognize faces and objects in photos posted to social networks, identify spoken words on Android phones, and translating online phone calls from one language to another. Google researchers Oriol Vinyals and Quoc Le built a system that could analyze existing conversations—in this case, movie dialogue—and teach itself to respond."Instead of using rules to build a conversational engine, we use a machine learning approach," Le tells WIRED. Other "chatbots" can carry on (somewhat) reasonable conversations with humans. There wasn't a team of software engineers who meticulously coded the bot to respond to certain questions in certain ways. Google detailed its project earlier this month in a research paper published to Arxiv, a popular repository for academic research.

Part of the trick is that this machine learned to converse by analyzing an enormous collection of old movie dialogue.

And there may be good reason it sounds like a movie.

It really is a human talking to a machine—a machine built by Google.

Neural nets are an old idea, but recently, after many years in exile from the AI community, they've risen to prominence—in enormous ways—now that companies like Google and Facebook and Microsoft have the computing power needed to run them.

"We let the machine learn from data rather than hand-coding the rules."The system uses what are called neural networks, vast networks of machines that approximate the web of neurons in the human brain.

He didn't think that neural nets would work so well with .