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Category: robotics/AI – Page 1,631

Recently, scientists designed an AI agent that learns 60% faster than its peers by combining quantum and classical computing. 📈

This week, an international collaboration led by Dr. Philip Walther at the University of Vienna took the “classic” concept of reinforcement learning and gave it a quantum spin. They designed a hybrid AI that relies on both quantum and run-of-the-mill classic computing, and showed that—thanks to quantum quirkiness—it could simultaneously screen a handful of different ways to solve a problem.

The result is a reinforcement learning AI that learned over 60 percent faster than its non-quantum-enabled peers. This is one of the first tests that shows adding quantum computing can speed up the actual learning process of an AI agent, the authors explained.

Although only challenged with a “toy problem” in the study, the hybrid AI, once scaled, could impact real-world problems such as building an efficient quantum internet. The setup “could readily be integrated within future large-scale quantum communication networks,” the authors wrote.

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In its preparation for great power competition, the US military is modernizing its artificial intelligence and machine learning techniques and testing them in West Africa.

by Scott Timcke

NIAMI, NIGER (Africa is a Country) — One striking feature of US military involvement in West Africa is the absence of an observable strategic vision for a desired end state. Nominally, US presence in the region’s multilayered conflicts revolves around building “security cooperation” with state partners to improve counterterrorism capabilities, ostensibly providing protection to communities that states cannot.

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It’s likely that safety drivers will remain in cabs for years to come as companies hone their sensor technology and train their software for every highway scenario. It’s expensive and painstaking work that can overwhelm even the best-run start-ups. The consensus within the industry is that three contestants stand the best chance to make it to the finish line: “It’s TuSimple, Aurora and Waymo,” says Grayson Brulte, co-founder of Brulte & Co., a consulting firm focused on transportation. TuSimple, a San Diego based-company that raised $1.35 billion in an initial public offering in April, is in the pole position, as Brulte sees it, because of its singular focus on trucking and its partnership, begun three years ago, with Navistar International to build autonomous trucks. “They’ve got the head start on it,” says Brulte.

These are the companies set to dominate the highways of tomorrow.

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Fully autonomous exploration and mapping of the unknown is a cutting-edge capability for commercial drones.

Drone autonomy is getting more and more impressive, but we’re starting to get to the point where it’s getting significantly more difficult to improve on existing capabilities. Companies like Skydio are selling (for cheap!) commercial drones that have no problem dynamically path planning around obstacles at high speeds while tracking you, which is pretty amazing, and it can also autonomously create 3D maps of structures. In both of these cases, there’s a human indirectly in the loop, either saying “follow me” or “map this specific thing.” In other words, the level of autonomous flight is very high, but there’s still some reliance on a human for high-level planning. Which, for what Skydio is doing, is totally fine and the right way to do it.

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The silicon Ouroboros.

TSMC produces chips for AMD, but it also now uses AMD’s processors to control the equipment that it uses to make chips for AMD (and other clients too). Sounds like a weird circulation of silicon, but that’s exactly what happens behind the scenes at the world’s largest third-party foundry.

There are hundreds of companies that use AMD EPYC-based machines for their important workloads, sometimes business-critical workloads. Yet, when it comes to mission-critical work, Intel Xeon (and even Intel Itanium and mainframes) rule the world. Luckily for AMD, things have begun to change, and TSMC has announced that it is now using EPYC-based servers for its mission-critical fab control operations.

“For automation with the machinery inside our fab, each machine needs to have one x86 server to control the operation speed and provision of water, electricity, and gas, or power consumption,” said Simon Wang, Director of Infrastructure and Communication Services Division at TSMC.

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SpaceX and NASA are targeting Saturday, May 1 at 8:35 p.m. EDT, or 00:35 UTC on May 2, for Dragon to autonomously undock from the International Space Station (ISS) and splashdown off the coast of Florida on Sunday, May 2 at approximately 2:57 a.m. EDT, 6:57 UTC, completing its first six-month operational mission to the Station.

A series of departure burns will move Dragon away from the orbiting laboratory, followed by the vehicle jettisoning the trunk to reduce weight and mass to help save propellant for the deorbit burn. Once complete, Dragon will re-enter Earth’s atmosphere and deploy its two drogue and four main parachutes in preparation for a soft water landing.

Aboard the spacecraft will be NASA astronauts Mike Hopkins, Victor Glover, Shannon Walker, and JAXA astronaut Soichi Noguchi, who flew to the space station on Dragon six months ago when Falcon 9 launched the spacecraft from historic Launch Complex 39A (LC-39A) at Kennedy Space Center in Florida on Sunday, November 15, 2020.

Upon splashdown, the Dragon and the astronauts will be quickly recovered and returned to Cape Canaveral and Houston respectively. Once the mission is complete, Dragon will be inspected and refurbished for future human spaceflight missions.

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It’s exactly as weird as it sounds.

The U.S. Army is looking into using animal muscle tissue as a means to move robots.

The Army Research Laboratory believes its bots could use real muscle, which allows most living things to move and manipulate their environments, instead of mechanical arms, wheels, tracks, and other systems to travel across the battlefield. The concept, which some might find disturbing, is an example of the new field of “biohybrids.”

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In order to effectively navigate real-world environments, legged robots should be able to move swiftly and freely while maintaining their balance. This is particularly true for humanoid robots, robots with two legs and a human-like body structure.

Building robots that are stable on their legs while walking can be challenging. In fact, legged robots typically have unstable dynamics, due to their pendulum-like structure.

Researchers at Hong Kong University of Science and Technology recently developed a computer vision-based robotic foot with tactile sensing capabilities. When integrated at the end of a ’s legs, the artificial foot can increase a robot’s balance and stability during locomotion.

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Yes, but they wont be trusted til 2035.

Current trends in AI use in healthcare lead me to posit that this market will significantly grow in the coming years. So, should leaders in healthcare expect the emergence of a fully automated electronic physician, sonographer or surgeon as a replacement for the human healthcare professional? Can the development of AI in healthcare help overcome the difficulties the industry faces today? To figure all this out, I would like to analyze the current challenges of using AI in healthcare.

Let’s discuss two promising examples: the application of AI in diagnosis and reading images, and the use of robotic systems in surgery.

Diagnostic Robots: Accuracy And Use For Treatment Recommendations

The success of AI in diagnosing is confirmed by the results of its application in a number of medical studies — for example, in optical coherence tomography (OCT), which requires serious qualifications. Google’s AI-based DeepMind Health system, for instance, demonstrates 94% accuracy of diagnoses for over 50 types of eye diseases in an early trial. Nevertheless, the system operates in conjunction with human experts.

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