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Archive for the ‘robotics/AI’ category: Page 2274

May 24, 2016

Powering nanotechnology with the world’s smallest engine

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

More information on ANTs.


In the minuscule world of nanotechnology, big steps are rare. But a recent development has the potential to massively improve our lives: an engine measuring 200 billionths of a metre, which could power tiny robots to fight diseases in living cells.

Life itself is proof of the extreme effectiveness of nanotechnology — the manipulation of matter on a molecular or atomic scale — in which DNA, proteins and enzymes can all be considered as machinery. In fact, researchers have managed to make micro-propellers using tiny strands of DNA. These strands can be stitched together so freely and precisely that the practise is known as “DNA origami”. However, DNA origami lacks force and operational speed (it takes time measurable in seconds), reducing its robotic function.

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May 23, 2016

New Chips Propel Machine Learning

Posted by in categories: computing, robotics/AI

Advances in microchips—particularly the graphics-processing units pioneered by Nvidia—are fueling growth in machine learning, a programming approach in which computers teach themselves without explicit instructions.

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May 22, 2016

Technique to Teach Robots New Tricks Developed: Study

Posted by in categories: computing, robotics/AI

As robots become more pervasive in society, humans will want them to do chores like cleaning the house or cooking, researchers said.

However, to get a robot started on a task, people who are not computer programmers will have to give it instructions, they said.

“We want everyone to be able to programme, but that is probably not going to happen,” said Matthew Taylor from Washington State University (WSU).

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May 21, 2016

Lethal Autonomous Weapons

Posted by in categories: biotech/medical, computing, drones, engineering, geopolitics, robotics/AI, treaties

Biography:
Stuart Russell received his B.A. with first-class honours in physics from Oxford University in 1982 and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is Professor (and formerly Chair) of Electrical Engineering and Computer Sciences and holder of the Smith-Zadeh Chair in Engineering. He is also an Adjunct Professor of Neurological Surgery at UC San Francisco and Vice-Chair of the World Economic Forum’s Council on AI and Robotics. He has published over 150 papers on a wide range of topics in artificial intelligence including machine learning, probabilistic reasoning, knowledge representation, planning, real-time decision making, multitarget tracking, computer vision, computational physiology, and global seismic monitoring. His books include “The Use of Knowledge in Analogy and Induction”, “Do the Right Thing: Studies in Limited Rationality” (with Eric Wefald), and “Artificial Intelligence: A Modern Approach” (with Peter Norvig).

Abstract:
Autonomous weapons systems select and engage targets without human intervention; they become lethal when those targets include humans. LAWS might include, for example, armed quadcopters that can search for and eliminate enemy combatants in a city, but do not include cruise missiles or remotely piloted drones for which humans make all targeting decisions. The artificial intelligence (AI) and robotics communities face an important ethical decision: whether to support or oppose the development of lethal autonomous weapons systems (LAWS).

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May 20, 2016

MIT researchers unveil perching bee robot

Posted by in categories: drones, robotics/AI

BOSTON, May 19 (UPI) — Engineers at MIT and Harvard have designed a tiny bee-like robot capable of pausing mid-flight to perch on a variety of objects before once again taking to the air. The robot uses static electricity to momentarily cling to the underside of objects.

Robots designed for aerial surveys and related observational tasks, like quadcopters, are currently limited by short flight times. They tend to run out of battery rather quickly. While perching won’t extend a drone’s actual time in the air, the technology could empower UAVs to employ their power more strategically — periodically taking a moment to rest their wings, or blades.

Researchers tested their technology on RoboBee, a bug-like flying robot no bigger than a quarter. A small jolt of static electricity emitted through a tiny foam patch on the bee’s head allows it to land on and adhere to the underside of a plant or to the ceiling.

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May 19, 2016

Google has patented a self-driving car that will glue people to the hood if you crash into them

Posted by in categories: robotics/AI, transportation

Hmmm, no thanks.


The glue would be covered by an outer layer that peels away during an accident.

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May 19, 2016

Inside Vicarious, the Secretive AI Startup Bringing Imagination to Computers

Posted by in categories: computing, robotics/AI

By reinventing the neural network, the company hopes to help computers make the leap from processing words and symbols to comprehending the real world.

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May 19, 2016

This Is Our First Good Look at Uber’s Self-Driving Car

Posted by in categories: engineering, robotics/AI, transportation

In a blog post today, Uber showed off the self-driving car that’s been stealthily cruising around Pittsburgh. The car is a hybrid Ford Fusion and is currently in early stages of safety testing. This particular Uber test vehicle was first spotted almost a year ago by local Pittsburgh media, but this is Uber’s first acknowledgement of such tests.

Uber and Google (among others) have been racing to be the first to develop self-driving taxis for over a year now. Uber “cleaned out” Carnegie Mellon and the National Robotics Engineering Center to be part of its Advanced Technology Center in Pittsburgh, the research arm responsible for developing this “look ma, no hands” technology. This heavy hiring out of Carnegie Mellon could give Uber a big boost. The Pittsburgh-based university considers itself the birthplace of self-driving cars, and it probably is. CMU researchers were testing autonomous vehicles before Google even existed.

In March, Uber also joined a coalition, this time in partnership with Google, to advocate for self-driving adoption.

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May 19, 2016

The Future Is Now for the Transhumanist Party

Posted by in categories: genetics, geopolitics, robotics/AI, transhumanism

This new SF Weekly story is one of the best long features on transhumanism I’ve ever read. It covers a myriad of futurist subjects. It’s out in print today too.


When John Lennon released “Imagine” in 1971, his lyrics about a brotherhood of man living life in peace struck many people as a simple, even anodyne, response to the Vietnam War. Although politically liberal, Lennon was no doctrinal Marxist — only three years earlier, his song “Revolution” had shrugged off people who “go carrying pictures of Chairman Mao.” But the song struck many evangelical Christians as ghoulish, and for some, “Imagine” eventually came to be a sort of national anthem for the repressively secular, globalist state that was thought to be emerging: the anti-Christian New World Order that later became talk-radio conspiracy theorist Alex Jones’ fever dream.

Left Behind, a series of 16 books written between 1995 and 2007 that details a possible end-of-the-world scenario, starting from when all good Christians go to heaven in an instant (the Rapture) until the Second Coming of Jesus Christ, specifically calls out “Imagine” as a weapon in Satan’s arsenal of seductive propaganda. The Antichrist in Left Behind is a suave, cosmopolitan Romanian named Nicolae Carpathia — the product of the fused sperm of two gay atheist academics, as it happens — who uses the global confusion in the aftermath of the Rapture to become Secretary General of the U.N. and eventually dictator of a world government that tattoos its citizens with the Mark of the Beast, damning them for eternity.

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May 18, 2016

Google supercharges machine learning tasks with TPU custom chip

Posted by in categories: computing, robotics/AI

Posted by norm jouppi, distinguished hardware engineer, google.

Machine learning provides the underlying oomph to many of Google’s most-loved applications. In fact, more than 100 teams are currently using machine learning at Google today, from Street View, to Inbox Smart Reply, to voice search.

But one thing we know to be true at Google: great software shines brightest with great hardware underneath. That’s why we started a stealthy project at Google several years ago to see what we could accomplish with our own custom accelerators for machine learning applications.

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