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Category: robotics/AI

Artificial intelligence is set to revolutionize the world, empowering those nations that fully harness its potential. The U.S. is still seen as the world AI leader, but China is catching up. The race is central to the U.S.-China rivalry and a critical facet of the economic and military competition that will define the decade.

#China2030 #AI #BloombergQuicktake.
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The MIT engineers are at it again — and this time, they’ve created a robotic cheetah that knows how to leap.

The designers installed a new system in the robot, dubbed the “mini cheetah,” that allows it to jump across gaps in the terrain, according to an MIT news release. The system relies on a real-time video sensor that detects potential obstacles like gaps and holes, and translates it into instructions on how the cheetah should react.

“In those settings, you need to use vision in order to avoid failure,” Gabriel Margolis, a professor of Computer Science and Artificial Intelligence at MIT, said in the release. “For example, stepping in a gap is difficult to avoid if you can’t see it. Although there are some existing methods for incorporating vision into legged locomotion, most of them aren’t really suitable for use with emerging agile robotic systems.”

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The sale of the world’s first Intelligent Collectibles & 10,000 Personality Pods (AI Souls) for NFTs has brought in almost 4,000 ETH netting approximately 17 million USD in Primary and Secondary Sales to build a community owned Intelligent Metaverse.

NEW YORK, October 20th 2021 — Alethea AI concluded their 7-day auction and direct sale for two historic collections:

I) a first of its kind collection, “The Revenants”, which are a collection of one hundred Intelligent NFTs on October 19th.

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As a robotics engineer, Yasemin Ozkan-Aydin, assistant professor of electrical engineering at the University of Notre Dame, gets her inspiration from biological systems. The collective behaviors of ants, honeybees and birds to solve problems and overcome obstacles is something researchers have developed in aerial and underwater robotics. Developing small-scale swarm robots with the capability to traverse complex terrain, however, comes with a unique set of challenges.

In research published in Science Robotics, Ozkan-Aydin presents how she was able to build multi-legged robots capable of maneuvering in challenging environments and accomplishing collectively, mimicking their natural-world counterparts.

“Legged robots can navigate challenging environments such as rough terrain and tight spaces, and the use of limbs offers effective body support, enables rapid maneuverability and facilitates obstacle crossing,” Ozkan-Aydin said. “However, legged robots face unique mobility challenges in terrestrial environments, which results in reduced locomotor performance.”

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Known formally as additive manufacturing, or AM, in the business, the process can make almost anything—even a car.

“For our OEMs, we were able to show a print rate 50% faster than they needed for value production and an assembly rate about 35% faster than they need for full-volume production,” Kevin said. “We have a dozen programs for multi component structures,” said Kevin. “Our first production programs are going to be in vehicles on the road in early 2022. And these are with brands that are within groups that are in the top five global automotive groups by annual volume.”

So, just to review, it’s: computer-designed parts, 3D printers making those parts, which are assembled by robots, in a much smaller space than typical assembly lines.

So no more River Rouge. The Czingers say that carmakers could replace assembly lines that had been a mile long with assembly stations like the one I saw, greatly reducing the lead time, cost, and complexity of car making. And you can switch the car model that you’re building with every new assembly. No more downtime during model-year changeover. And all those spare parts carmakers have to keep in warehouses for 10 years? They will be replaced by instant 3D printing of whatever spare part you need.

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Deep North, a Foster City, California-based startup applying computer vision to security camera footage, today announced that it raised $16.7 million in a Series A-1 round. Led by Celesta Capital and Yobi Partners, with participation from Conviction Investment Partners, Deep North plans to use the funds to make hires and expand its services “at scale,” according to CEO Rohan Sanil.

Deep North, previously known as Vmaxx, claims its platform can help brick-and-mortar retailers “embrace digital” and protect against COVID-19 by retrofitting security systems to track purchases and ensure compliance with masking rules. But the company’s system, which relies on algorithms with potential flaws, raises concerns about both privacy and bias.

Full Story:

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Nvidia announced today that Isaac, its developer toolbox for supporting AI-powered robotics, will deepen support of the Robot Operating System (ROS). The announcement is being made this morning at ROS World 2,021 a conference for developers, engineers, and hobbyists who work on ROS, a popular open-source framework that helps developers build and reuse code used for robotics applications.

Nvidia, which is trying to assert its lead as a supplier of processors for AI applications, announced a host of “performance perception” technologies that would be part of what it will now call Isaac ROS. This includes computer vision and AI/ML functionality in ROS-based applications to support things like autonomous robots.

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A new control system, demonstrated using MIT’s robotic mini cheetah, enables four-legged robots to jump across uneven terrain in real-time. A loping cheetah dashes across a rolling field, bounding over sudden gaps in the rugged terrain. The movement may look effortless, but getting a robot to move this way is an altogether different prospect.

In recent years, four-legged robots inspired by the movement of cheetahs and other animals have made great leaps forward, yet they still lag behind their mammalian counterparts when it comes to traveling across a landscape with rapid elevation changes.

“In those settings, you need to use vision in order to avoid failure. For example, stepping in a gap is difficult to avoid if you can’t see it. Although there are some existing methods for incorporating vision into legged locomotion, most of them aren’t really suitable for use with emerging agile robotic systems,” says Gabriel Margolis, a PhD student in the lab of Pulkit Agrawal, professor in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT.

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