Category: robotics/AI – Page 2389
To me; it’s all common sense. If you step back look at the technology landscape as a whole along with AI; you start to see the barriers that truly spolights where we have way too much hype around AI.
Example, hacking. If we had truly advance AI at the level that it has been promoted; wouldn’t make sense that researchers would want to solve the $120 billion dollar money pit issue around Cyber Security and make billions to throw at their emerging AI tech plus ensure their AI investment wouldn’t incur pushback by consumers due to lack of trust that AI would not be hacked? So, I usually tread litely on over hype technologies.
I do see great possiblities and seen some amazing things and promise from Quantum Computing; however, we will not truly realize its impact and full potential until another 7 years; I will admit I see more promise with it than the existing AI landscape that is built off of existing traditional digital technology that has been proven to be broken by hackers.
Do you “believe” in AI?
The science fiction world is full of Artificial Intelligence (AI), but AI reality is still far away. According to an article featured in Technology Review, technology is still suffering and nowhere near the expectations of AI.
Senior editor for AI at MIT Technology Review, Will Knight wrote, “For all the remarkable progress being made in artificial intelligence, and warnings about the upheaval this might bring, the smartest computer would still struggle to make it through the eighth grade.”
Knight relates how programmers competed in an Allen Institute for Artificial Intelligence (AI2) contest. The programmers were challenged to write computer programs that could take a science test that was eighth-grade level. During the annual Association for the Advancement of Artificial Intelligence (AAAI) meeting, the winner was announced.
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This is extremely interesting and innovating to me. Why? Just imagine if your car (even a self driving car) your car breaks down on a road somewhere 10 to 25 miles away from the nearest gas station or town. And, you have a backup system that alerts you in the car that it has to switch over to tow mode, and engages a robotic pull system and set your flashers on then tows you to the nearest gas station or police station; etc.? No more tow bills, no more fears to the elderly or others being exposed on the side of the road. BTW — the car engine keeps the car microbot/s charged up.
A team of tiny robot ants pull a car that is thousands of times their weight as part of an experiment at Stanford University.
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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.
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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