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Category: robotics/AI – Page 2,048

Google’s new lab is indicative of a broader effort to bring so-called machine learning to robotics. Researchers are exploring similar techniques at places like the University of California, Berkeley, and OpenAI, the artificial intelligence lab founded by the Silicon Valley kingpins Elon Musk and Sam Altman. In recent months, both places have spawned start-ups trying to commercialize their work.

In 2013, the company started an ambitious, flashy effort to create robots. Now, its goals are more modest, but the technology is subtly more advanced.

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We interviewed Andrew Yang, a Democratic candidate for president of the United States who has made an answer to automation one of the central issues of his campaign. The tech-minded candidate shares his thoughts on drones, geo-engineering, asteroid detection, space force and more!

#AndrewYang #Yang2020 #WhatTheFuture

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As the artificial brain races towards the singularity, what we often forget is the boost to human brainpower that will accompany it. As we increase our senses and perceptions, humans have a choice what to do with these new superpowers, that can be used to reinforce one’s tunnel vision of life or to ignore it.

This story is part of What Happens Next, our complete guide to understanding the future. Read more predictions about the Future of Fact.

Not everyone experiences the world in the same way. Whether it’s how you react to the results of an election or what tones you hear in a sound clip, observable reality is often not as objective as you think it is.

Emerging technologies such as augmented reality will further blur this line. With AR on mobile devices and head-mounted displays, we’re well within the start of what it means to live an augmented life. Humans are doing a lot of fun things right now, like integrating playful games into our world and painting ourselves with digitally applied effects and makeup. We’re also starting to find utility for AR in the workplace and with hardware designed specifically for the enterprise market.

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Image: Business Wire

Over half of the 415 vulnerabilities found in industrial control systems (ICS) were assigned CVSS v.3.0 base scores over 7 which are designated to security issues of high or critical risk levels, with 20% of vulnerable ICS devices being impacted by critical security issues.

As detailed in Kaspersky’s “Threat landscape or industrial automation systems H2 2018”, “The largest number of vulnerabilities affect industrial control systems that control manufacturing processes at various enterprises (115), in the energy sector (110), and water supply (63).”

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Livingston is sitting comfortably in his office in Portland, Oregon, when he appears on the screens inside the car and announces he’ll be our teleoperator this afternoon. A moment later, the MKZ pulls into traffic, responding not to the man in the driver’s seat, but to Livingston, who’s sitting in front of a bank of screens displaying feeds from the four cameras on the car’s roof, working the kind of steering wheel and pedals serious players use for games like Forza Motorsport. Livingston is a software engineer for Designated Driver, a new company that’s getting into teleoperations, the official name for remotely controlling self- driving vehicles.

Designated Driver is just the latest competitor to enter the market for the teleoperation tech that will make robo-cars work.

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Dr. Been Kim wants to rip open the black box of deep learning.

A senior researcher at Google Brain, Kim specializes in a sort of AI psychology. Like cognitive psychologists before her, she develops various ways to probe the alien minds of artificial neural networks (ANNs), digging into their gory details to better understand the models and their responses to inputs.

The more interpretable ANNs are, the reasoning goes, the easier it is to reveal potential flaws in their reasoning. And if we understand when or why our systems choke, we’ll know when not to use them—a foundation for building responsible AI.

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Yoshua Bengio, Geoffrey Hinton, and Yann LeCun — sometimes called the ‘godfathers of AI’ — have been recognized with the $1 million annual prize for their work developing the AI subfield of deep learning. The techniques the trio developed in the 1990s and 2000s enabled huge breakthroughs in tasks like computer vision and speech recognition. Their work underpins the current proliferation of AI technologies, from self-driving cars to automated medical diagnoses.

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