People don’t feel pressure or obligation when talking to a robot.
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Category: robotics/AI
Roaches are speedy, agile, and nearly indestructible—which is why engineers are so interested in them.
Robots can look like just about anything: people, dinosaurs, quadcopters—you name it. So why would anyone design a robot that looks like one of the grossest and most detested species on the planet?
Well, like cephalopods, roaches’ bodies gives them distinct, if squirm-worthy, advantages—namely, the ability to become nearly two-dimensional to squeeze through cracks and under doors. Cockroaches can flatten themselves to a one-tenth of an inch and can bear loads 900 times heavier than they are (which is why we have to stomp on them extra hard). Perhaps most impressive is their ability to scurry along at top speed when compressed to half their normal height. These attributes make roaches nimble, persistent, and hardy—three supremely useful qualities for a robot, and three reasons scientists have pursued the development of robo-roaches.
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CHAMPAIGN, Ill. — A new class of miniature biological robots, or bio-bots, has seen the light — and is following where the light shines.
The bio-bots are powered by muscle cells that have been genetically engineered to respond to light, giving researchers control over the bots’ motion, a key step toward their use in applications for health, sensing and the environment. Led by Rashid Bashir, the University of Illinois head of bioengineering, the researchers published their results in the Proceedings of the National Academy of Sciences.
“Light is a noninvasive way to control these machines,” Bashir said. “It gives us flexibility in the design and the motion. The bottom line of what we are trying to accomplish is the forward design of biological systems, and we think the light control is an important step toward that.”
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Interesting position that IBM is taking with Quantum Computing. The one challenge that was highlighted in this article around unstable particles actually has been in the process of being resolved by Charles Marcus and colleagues at the University of Copenhagen’s Niels Bohr Institute; Univ. of Copenhagan’s report came out a few weeks ago and it may be a good thing for IBM to connect with the University so they can see how this was resolved.
Also, I don’t believe that we have 3 uniquely different platforms of Quantum as this article highlights. Trying to state that a D-Wave Quantum Computer is not a full Quantum platform or less of a Quantum Platform to is not a fair statement; and I encourage others to pull back from that perspective at this point until Quantum Computing is more evolved and standards around the platform is well defined and approved by industry. Also, the Gartner graph in this article is not one that I embraced given the work on Quantum is showing us the we’re less than 10 yrs away for it in the mainstream instead of Gartners graph showing us Quantum will require more than 10 years to hit the mainstream. And, I saw some of missed marks on Bio-sensors and BMI technology taking more than 10 years on the Gartner graph which is also incorrect since we hearing this week announcements of the new bio-chips which enables bio-sensors and BMIs are making some major steps forward with various devices and implants.
The 3 Types Of Quantum Computers And Their Applications by Jeff Desjardins, Visual Capitalist
It’s an exciting time in computing.
Just days ago, Google’s AlphaGo AI took an insurmountable lead in the 3,000 year-old game of Go against the reigning world champion, Lee Sedol. In a five-game series, the score is now 3–1 for the machine with one game left on March 15, 2016 in Seoul, South Korea.
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Or not.
It was hailed as the most significant test of machine intelligence since Deep Blue defeated Garry Kasparov in chess nearly 20 years ago. Google’s AlphaGo has won two of the first three games against grandmaster Lee Sedol in a Go tournament, showing the dramatic extent to which AI has improved over the years. That fateful day when machines finally become smarter than humans has never appeared closer—yet we seem no closer in grasping the implications of this epochal event.
Indeed, we’re clinging to some serious—and even dangerous—misconceptions about artificial intelligence. Late last year, SpaceX co-founder Elon Musk warned that AI could take over the world, sparking a flurry of commentary both in condemnation and support. For such a monumental future event, there’s a startling amount of disagreement about whether or not it’ll even happen, or what form it will take. This is particularly troubling when we consider the tremendous benefits to be had from AI, and the possible risks. Unlike any other human invention, AI has the potential to reshape humanity, but it could also destroy us.
It’s hard to know what to believe. But thanks to the pioneering work of computational scientists, neuroscientists, and AI theorists, a clearer picture is starting to emerge. Here are the most common misconceptions and myths about AI.
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Stanford’s μTug minibots are on a roll lately.
The latest battery of experiments at Stanford’s Biomimetics and Dextrous Manipulation Lab dealt with harnessing the power of ants in robot form— specifically, researchers hoped to replicate ants’ ability to work together to haul very heavy objects. In the experiments, robots that jump or walk with a quick, jerky force were quickly determined to be inefficient in groups, while the μTugs won out due to the longer duration of pulling force they were able to create with their tiny winches. If you’ve ever played tug of war than this strategy already makes intrinsic sense. Not only could the μTug smimc ants through teamwork, but they anchored themselves to the ground with an adhesive borrowed from gecko toes.
To prove just how powerful the robots are, scientists took a group of six μTugs—which can pull up to 52 pounds each —and had them move a full-sized car with a passenger inside. Did we mention the passenger was the author of the research paper? When those things start self-replicating, he’s going to be the first one they come after.
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A master player of the game Go has won his first match against a Google computer program, after losing three in a row in a best-of-five competition.
Lee Se-dol, one of the world’s top players, said his win against AlphaGo was “invaluable”.
The Chinese board game is considered to be a much more complex challenge for a computer than chess, and AlphaGo’s wins were seen as a landmark moment for artificial intelligence.
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