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They are.
The cyborgs are upon us. Turns out, they’re more ‘enhanced reality’ and less ‘science fiction.’
In 1998, Professor of Cybernetics Kevin Warwick had a chip implanted in his body that would open electronic doors and turn on lights as he passed. In 2002, he had a 100 electrode array wired into the nervous system of his arm to allow him to remotely control an artificial hand. Today, he’s working on using animal brain cells as a control system for robots.
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And it looks like a big yak.
China’s state media, the Global Times, claims the country has developed the world’s largest electric-powered quadruped bionic robot. And to be honest, that thing looks just like a yak.
Bizarre appearances aside, this comes as the latest in China’s push to become a global leader in robotics by 2025. And also, of course, in military tech.… See more.
Continue reading “China’s New Electric Quadruped Robot Could Be the Largest in the World” »
Made from the stem cells of a frog, are tiny living machines. And researchers have just debuted version 2.0.
Digital Twins are virtual models of the physical world. They use the Internet of Things, artificial intelligence and complex data in models that create insights and support (real-time) decision making. It is perhaps healthcare that holds the greatest potential for Digital Twins.
China has introduced what it claims to be the world’s largest electrically-powered quadruped robot to assist the military on logistics and reconnaissance missions.
With a “yak-like appearance,” the four-legged robot can reportedly carry up to 352 pounds (160 kilograms) of payload and run at six miles (10 kilometers) per hour.
Continue reading “China Unveils ‘World’s Largest’ Quadruped Military Robot” »
Mock seemed pleased with the outcome. “You could look at this and say, ‘O.K., the A.I. got five, our human got zero,’” he told viewers. “From the fighter-pilot world, we trust what works, and what we saw was that in this limited area, this specific scenario, we’ve got A.I. that works.” (A YouTube video of the trials has since garnered half a million views.)
Brett Darcey, who runs Heron, told me that the company has used Falco to fly drones, completing seventy-four flights with zero crashes. But it’s still unclear how the technology will react to the infinite possibilities of real-world conditions. The human mind processes more slowly than a computer, but it has the cognitive flexibility to adapt to unimagined circumstances; artificial intelligence, so far, does not. Anna Skinner, a human-factors psychologist, and another science adviser to the ACE program, told me, “Humans are able to draw on their experience and take reasonable actions in the face of uncertainty. And, especially in a combat situation, uncertainty is always going to be present.”
What’s next? Human brain-scale AI.
Funded by the Slovakian government using funds allocated by the EU, the I4DI consortium is behind the initiative to build a 64 AI exaflop machine (that’s 64 billion, billion AI operations per second) on our platform by the end of 2022. This will enable Slovakia and the EU to deliver for the first time in the history of humanity a human brain-scale AI supercomputer. Meanwhile, almost a dozen other countries are watching this project closely, with interest in replicating this supercomputer in their own countries.
There are multiple approaches to achieve human brain-like AI. These include machine learning, spiking neural networks like SpiNNaker, neuromorphic computing, bio AI, explainable AI and general AI. Multiple AI approaches require universal supercomputers with universal processors for humanity to deliver human brain-scale AI.
Advances in the AI realm are constantly coming out, but they tend to be limited to a single domain: For instance, a cool new method for producing synthetic speech isn’t also a way to recognize expressions on human faces. Meta (AKA Facebook) researchers are working on something a little more versatile: an AI that can learn capably on its own whether it does so in spoken, written or visual materials.
The traditional way of training an AI model to correctly interpret something is to give it lots and lots (like millions) of labeled examples. A picture of a cat with the cat part labeled, a conversation with the speakers and words transcribed, etc. But that approach is no longer in vogue as researchers found that it was no longer feasible to manually create databases of the sizes needed to train next-gen AIs. Who wants to label 50 million cat pictures? Okay, a few people probably — but who wants to label 50 million pictures of common fruits and vegetables?
Currently some of the most promising AI systems are what are called self-supervised: models that can work from large quantities of unlabeled data, like books or video of people interacting, and build their own structured understanding of what the rules are of the system. For instance, by reading a thousand books it will learn the relative positions of words and ideas about grammatical structure without anyone telling it what objects or articles or commas are — it got it by drawing inferences from lots of examples.
Keeping up with the first law of robotics: a new photonic effect for accelerated drug discovery. Physicists at the University of Bath and University of Michigan demonstrate a new photonic effect in semiconducting nanohelices. A new photonic effect in semiconducting helical particles with nanos.
California has more rooftops with solar panels than any other state and continues to be a leader in new installations. It is also first in terms of the percentage of the state’s electricity coming from solar, and third for solar power capacity per capita. However, former California governor Arnold Schwarzenegger has expressed concerns that California.
