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Category: robotics/AI – Page 2099

Self-driving cars have plenty of benefits — but the American public still doesn’t trust them. A report from the American Automobile Association released Tuesday shows that 73 percent of drivers would be too afraid to ride in a self-driving car, a marked jump from the 63 percent reported late last year, with millennial distrust jumping from 49 percent to 64 percent over the same period.

The results of the survey come despite autonomous-vehicle makers reporting strong signs of progress. Waymo, which started life as Google’s self-driving car project, announced in March that it’s accumulated over 5 billion miles in virtual driving and 5 million miles in real-world driving, after opening its autonomous minivan service to the public last year. Tesla CEO Elon Musk, who said in February he’s “pretty excited about how much progress we’re making on the neural net front,” has predicted autonomous driving for existing vehicles could surface in a matter of months. Companies like Aurora are predicting their systems could hit the markets in 2021.

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Scientists at the University of Alberta have applied a machine learning technique using artificial intelligence to perfect and automate atomic-scale manufacturing, something which has never been done before. The vastly greener, faster, smaller technology enabled by this development greatly reduces impact on the climate while still satisfying the insatiable demands of the information age.

“Most of us thought we’d never be able to automate atomic writing and editing, but stubborn persistence has paid off, and now Research Associate Moe Rashidi has done it,” said Robert Wolkow, professor of physics at the University of Alberta, who along with his Research Associate has just published a paper announcing their findings.

“Until now, we printed with about as efficiently as medieval monks produced books,” explained Wolkow. “For a long while, we have had the equivalent of a pen for writing with atoms, but we had to write manually. So we couldn’t mass produce atom-scale devices, and we couldn’t commercialize anything. Now that has all changed, much like the disruption following the arrival of the printing press for those medieval monks. Machine learning has automated the atom fabrication process, and an atom-scale manufacturing revolution is sure to follow.”

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Over the last few years, Google and Coursera have regularly teamed up to launch a number of online courses for developers and IT pros. Among those was the Machine Learning Crash course, which provides developers with an introduction to machine learning. Now, building on that, the two companies are launching a machine learning specialization on Coursera. This new specialization, which consists of five courses, has an even more practical focus.

The new specialization, called “Machine Learning with TensorFlow on Google Cloud Platform,” has students build real-world machine learning models. It takes them from setting up their environment to learning how to create and sanitize datasets to writing distributed models in TensorFlow, improving the accuracy of those models and tuning them to find the right parameters.

As Google’s Big Data and Machine Learning Tech Lead Lak Lakshmanan told me, his team heard that students and companies really liked the original machine learning course but wanted an option to dig deeper into the material. Students wanted to know not just how to build a basic model but also how to then use it in production in the cloud, for example, or how to build the data pipeline for it and figure out how to tune the parameters to get better results.

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The Robots are Coming!

European consumers expect a clean supply chain and biodiversity to be conserved. Therefore, reducing the inputs of pesticides and chemical fertilisers to a minimum and/or replacing them by agro-ecological or robot solutions is required. Furthermore, the average age of European farmers is among the highest of all sectors, thus farming needs to attract young people with attractive working opportunities.

This is where the new agricultural robot solution for precision farming developed within the context of the EU Flourish (Aerial Data Collection and Analysis, and Automated Ground Intervention for Precision Farming) project can play a part. Use of robots in precision farming has the potential not only to increase yield, but also to reduce the reliance on fertilisers, herbicides and pesticides through selectively spraying individual plants or through weed removal.

Helping farmland flourish

Continue reading “New robots set to transform farming” | >

When history’s pilgrims and pioneers arrived in a new territory, they used the land’s natural resources to build their settlements. Space colonists, on the other hand, will have to bring materials from Earth and assemble them on Mars. Andrew Rush, president and CEO of space-based manufacturing firm Made In Space, believes the process of creating off-world infrastructure will be similar to building IKEA furniture. Only the parts will be made with an advanced 3D printer and put together by an autonomous robot.

“We think the future of in-space operation is one of manufacturing and assembly, just like how you built the table you’re sitting on right now,” Rush says. “That table is a multi-material object, and its pieces were all manufactured in different ways. I don’t think space colonies are going to take a different approach.”

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France isn’t alone. Last month, the European Union’s executive branch recommended its member states increase their public and private sector investment in AIt also pledged billions in direct research spending. Meanwhile, China laid out its AI plan for global dominance last year, a plan that has also been backed up with massive investment. China’s goal is to lead the world in AI technology by 2030. Around the world, our global economic competitors are taking action on artificial intelligence.

Opinion: Rep. John K. Delaney argues that if the United States wants a prosperous economy, it needs a national plan for artificial intelligence.

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Microsoft has purchased startup company Semantic Machines in an effort to make artificial intelligence bots sound more human. The Berkeley, California-based business focuses on contextual understanding of conversation.

Previously, the firm has worked with Apple on speech recognition technology for Siri. Semanitc Machines is lead by professor Dan Klein of UC Berkeley and professor Percy Liang of Standford University in addition to Apple’s former chief speech scientist Larry Gillick.

Microsoft has been working on speech recognition and natural language processing for nearly two decades now. As Cortana has gained a more prominent role in recent years, Redmond is aiming to improve the accuracy and fluency of its assistant.

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Machine-learning technology is growing ever more accessible. Let’s not have a 9/11-style ‘failure of imagination’ about it.

There is a general tendency among counterterrorism analysts to understate rather than hyperbolize terrorists’ technological adaptations. In 2011 and 2012, most believed that the “Arab Spring” revolutions would marginalize jihadist movements. But within four years, jihadists had attracted a record number of foreign fighters to the Syrian battlefield, in part by using the same social media mobilization techniques that protesters had employed to challenge dictators like Zine El Abidine Ben Ali, Hosni Mubarak, and Muammar Qaddafi.

Militant groups later combined easy accessibility to operatives via social media with new advances in encryption to create the “virtual planner” model of terrorism. This model allows online operatives to provide the same offerings that were once the domain of physical networks, including recruitment, coordinating the target and timing of attacks, and even providing technical assistance on topics like bomb-making.

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