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Archive for the ‘robotics/AI’ category: Page 2067

Jun 16, 2017

When artificial intelligence is bad news for the boss

Posted by in categories: business, economics, information science, robotics/AI

The two academic authors from Massachusetts Institute of Technology, who became the pin-up boys of the Davos crowd for their previous book on The Second Machine Age (2014), do a neat job of scanning the technological horizon and highlighting significant landmarks. This is a clear and crisply written account of machine intelligence, big data and the sharing economy. But McAfee and Brynjolfsson also wisely acknowledge the limitations of their futurology and avoid over-simplification. No one can really have much idea how the business world is going to evolve or predict the precise interplay between all these fast-changing forces.


A new book by the authors of ‘The Second Machine Age’ suggests that digital disruption is coming to the corner office.

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Jun 16, 2017

400 Burger Per Hour Robot Will Put Teenagers Out Of Work

Posted by in categories: employment, robotics/AI

Just a quick heads up, high school students. You might want to save your job application efforts for retail gigs, because the fast food space is about to be invaded by robots.

We already showed you an autonomous grillmaster that can monitor and flip an entire grill full of patties. Today’s bot is even more versatile. Not only can it cook the patty, but it can also dice up fresh toppings like tomatoes, pickles, and onions… and it can even deftly stack everything on a toasted bun.

This autonomous marvel was designed and built by Momentum Machines, who just wrapped up a successful funding round to the tune of $18 million. It’s pretty clear why they attracted so much cash.

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Jun 16, 2017

This Startup Is Disrupting The Construction Industry With 3D-Printing Robots

Posted by in categories: 3D printing, robotics/AI

Cazza’s 3D printing robots has introduced a new way of construction, which is more eco-friendly and cost-effective than traditional methods.

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Jun 15, 2017

Swimming robot to probe damage at Japan nuclear plant

Posted by in categories: nuclear energy, robotics/AI

YOKOSUKA, Japan (AP) — A Japanese industrial group unveiled Thursday a robot designed for underwater probes of damage from meltdowns at the Fukushima Dai-Ichi nuclear plant after the March 2011 earthquake and tsunami.

Remote controlled robots are key to the decades-long decommissioning process for the plant. But super-high radiation and structural damage inside the reactors hampered earlier attempts to inspect areas close to the reactors’ cores.

The developers say they plan to send the new “mini manbo,” or “little sunfish,” probe into the primary containment vessel of Unit 3 at Fukushima in July to study the extent of damage and locate parts of melted fuel thought to have fallen to the bottom of the chamber, submerged by highly radioactive water.

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Jun 15, 2017

What is a Drone? (Future A to Z)

Posted by in categories: automation, computing, drones, electronics, military, nuclear weapons, robotics/AI

Drones. Drone is a word you see pretty often in today’s pop culture. But drones seem to be an extremely diverse species. Even flightless vehicles are occasionally referred to as drones. So what exactly is a drone?

In this video series, the Galactic Public Archives takes bite-sized looks at a variety of terms, technologies, and ideas that are likely to be prominent in the future. Terms are regularly changing and being redefined with the passing of time. With constant breakthroughs and the development of new technology and other resources, we seek to define what these things are and how they will impact our future.

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Jun 14, 2017

Father of deep learning AI on General purpose AI and AI to conquer space in the 2050s

Posted by in categories: robotics/AI, space

Juergen Schmidhuber is the father of Deep learning Artificial Intelligence.

Since age 15 or so, the main goal of professor Jürgen Schmidhuber has been to build a self-improving Artificial Intelligence (AI) smarter than himself, then retire. His lab’s Deep Learning Neural Networks (NNs) (since 1991) and Long Short-Term Memory have transformed machine learning and AI, Deep Learning since 1991 – Winning Contests in Pattern Recognition and Sequence Learning Through Fast and Deep / Recurrent Neural Networks and are now (2017) available to billions of users through the world’s most valuable public companies including Google, Apple, Microsoft, Amazon, etc. In 2011, his team was the first to win official computer vision contests through deep NNs, with superhuman performance. His research group also established the field of mathematically rigorous universal AI and recursive self-improvement in universal problem solvers that learn to learn (since 1987).

Continue reading “Father of deep learning AI on General purpose AI and AI to conquer space in the 2050s” »

Jun 13, 2017

A Hybrid of Quantum Computing and Machine Learning Is Spawning New Ventures

Posted by in categories: quantum physics, robotics/AI

At the intersection of two challenging computational and technological problems, may lie the key better understanding and manipulating quantum randomness.

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Jun 13, 2017

The Grocery Store of the Future is Mobile, Self-Driving, and Run by AI

Posted by in categories: robotics/AI, transportation

Can the Moby store bring locally controlled convenience stores to places that lack a simple place to buy essentials?

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Jun 13, 2017

Why is the language of transhumanists and religion so similar?

Posted by in categories: robotics/AI, singularity, transhumanism

Very interesting new feature in Aeon on AI that also discusses my short fiction The Jesus Singularity: https://aeon.co/essays/why-is-the-language-of-transhumanists…so-similar #transhumanism


The most avid believers in artificial intelligence are aggressively secular – yet their language is eerily religious. Why?

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Jun 13, 2017

Nanophotonic system allows optical ‘deep learning’

Posted by in categories: biotech/medical, robotics/AI

“Deep Learning” computer systems, based on artificial neural networks that mimic the way the brain learns from an accumulation of examples, have become a hot topic in computer science. In addition to enabling technologies such as face- and voice-recognition software, these systems could scour vast amounts of medical data to find patterns that could be useful diagnostically, or scan chemical formulas for possible new pharmaceuticals.

But the computations these systems must carry out are highly complex and demanding, even for the most powerful computers.

Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. Their results appear today in the journal Nature Photonics (“Deep learning with coherent nanophotonic circuits”) in a paper by MIT postdoc Yichen Shen, graduate student Nicholas Harris, professors Marin Soljacic and Dirk Englund, and eight others.

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