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Ubiquitous, mobile supercomputing. Artificially-intelligent robots. Self-driving cars. Neuro-technological brain enhancements. Genetic editing. The evidence of dramatic change is all around us and it’s happening at exponential speed.

Previous industrial revolutions liberated humankind from animal power, made mass production possible and brought digital capabilities to billions of people. This Fourth Industrial Revolution is, however, fundamentally different. It is characterized by a range of new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human.

http://www.weforum.org/

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With 3D printers (like the one in India) printing buildings while leveraging AI technology we could see the building of complexes in space v. needing an inflatable room.


NASA on Saturday successfully expanded and pressurized an add-on room at the International Space Station two days after aborting the first attempt when it ran into problems.

The flexible habitat, known as the Bigelow Expandable Activity Module (BEAM), completed slowly extending 67 inches (170 centimeters) at 4:10 pm (2010 GMT) following more than seven hours during which astronaut Jeff Williams released short blasts of air into the pod’s walls from the orbiting lab using a manual valve.

After the expansion was completed, he opened eight air tanks inside BEAM, pressurizing the pod to a level close to the space station’s 14.7 pounds per square inch.

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Awesome.


The 3D-printed office was constructed using a special mixture of cement and a set of building material designed and made in the UAE and the United States. To ensure reliability, the materials have undergone a range of tests in both China and the United Kingdom.

A 3D-printer measuring 20-feet high, 120-feet long and 40-feet wide was used to print the building that featured an automated robotic arm to implement printing process.

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LAPEER COUNTY, MI – U.S. Army convoys are set to roll down the interstate in Lapeer and St. Clair counties as part of a first-time testing of driverless military vehicle equipment on public roadways in the state.

If successful, officials say the technology that may save the lives of soldiers thousands of miles away.

Representatives from the U.S. Army Tank Automotive Research Development and Engineering Center, or TARDEC, and Michigan Department of Transportation met with residents in Imlay City and Capac on May 23 to discuss the testing scheduled for late June along Interstate 69.

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One misstep after another for Boston Dynamics. First they get bought by the bunglers at Google, who dont want to do business with the Pentagon, so they buy a company who almost exclusively works for the Pentagon, and now getting sold to a foreign electronics company.

Pretty sad treatment for the company making some of the best robotics in the world. It should be sold to a US defense contractor.


Google is selling off robotics company Boston Dynamics, and Toyota is a serious contender.

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Shutterstock.

Can we really have a conversation with a bot? Voice assistants like Siri, Cortana and Google Now make a good attempt at it, but these are still clearly machines. Their level of artificial intelligence is far behind human intellect. But you can bet Google is working on improving AI.

Renown author Ray Kurzweil has revealed him and his team have been working with Google to create chatbots. These are said to be advanced bots with which you can have ‘interesting conversations’.

Not much else was revealed, but Kurzweeil did specify one of these would be based off one of his book’s characters — Danielle. But these chatbots won’t be limited to specific personalities.

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Fun stuff.


What are the fundamental limitations inherent in machine learning systems?

That’s the central question of a potential new DARPA program known as the Fundamental Limits of Learning (Fun LoL) which according to the researchers will address how the quest for the ultimate learning machine can be measured and tracked in a systematic and principled way.

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“It’s not easy to put the intelligence in artificial intelligence. Current machine learning techniques generally rely on huge amounts of training data, vast computational resources, and a time-consuming trial and error methodology. Even then, the process typically results in learned concepts that aren’t easily generalized to solve related problems or that can’t be leveraged to learn more complex concepts. The process of advancing machine learning could no doubt go more efficiently—but how much so? To date, very little is known about the limits of what could be achieved for a given learning problem or even how such limits might be determined,” DARPA stated.

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