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Four-legged robots are nothing novel — Boston Dynamics’ Spot has been making the rounds for some time, as have countless alternative open source designs. But with theirs, researchers at MIT claim to have broken the record for the fastest robot run recorded. Working out of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), the team says that they developed a system that allows the MIT-designed Mini Cheetah to learn to run by trial and error in simulation.

While the speedy Mini Cheetah has limited direct applications in the enterprise, the researchers believe that their technique could be used to improve the capabilities of other robotics systems — including those used in factories to assemble products before they’re shipped to customers. It’s timely work as the pandemic accelerates the adoption of autonomous robots in industry. According to an Automation World survey, 44.9% of the assembly and manufacturing facilities that currently use robots consider the robots to be an integral part of their operations.

Today’s cutting-edge robots are “taught” to perform tasks through reinforcement learning, a type of machine learning technique that enables robots to learn by trial and error using feedback from their own actions and experiences. When a robot performs a “right” action — i.e., an action that’ll lead it toward a desired goal, like stowing an object on a shelf — it receives a “reward.” When it makes a mistake, the robot either doesn’t receive a reward or is “punished” by losing a previous reward. Over time, the robot discovers ways to maximize its reward and perform actions that achieve the sought-after goal.

The researchers simulated the molecules H4, molecular nitrogen, and solid diamond. These involved as many as 120 orbitals, the patterns of electron density formed in atoms or molecules by one or more electrons. These are the largest chemistry simulations performed to date with the help of quantum computers.

A classical computer actually handles most of this fermionic quantum Monte Carlo simulation. The quantum computer steps in during the last, most computationally complex step—calculating the differences between the estimates of the ground state made by the quantum computer and the classical computer.

The prior record for chemical simulations with quantum computing employed 12 qubits and a kind of hybrid algorithm known as a variational quantum eigensolver (VQE). However, VQEs possess a number of limitations compared with this new hybrid approach. For example, when one wants a very precise answer from a VQE, even a small amount of noise in the quantum circuitry “can cause enough of an error in our estimate of the energy or other properties that’s too large,” says study coauthor William Huggins, a quantum physicist at Google Quantum AI in Mountain View, Calif.

Combining multiple data streams into one feed could speed up networks and let them tackle more than one task at a time.

Mitsubishi’s AI not only improves performance, it also fosters trust.

Mitsubishi’s Electric AI not only improves performance, it also fosters trust.

The smartest Scientists of both China and the United States are working hard on creating the fastest hardware for future Supercomputers in the exaflop and zettaflop performance range. Companies such as Intel, Nvidia and AMD are continuing Moore’s Law with the help of amazing new processes by TSMC. These supercomputers are secret projects by the government in hopes of beating each other in the tech industry and to prepare for Artificial Intelligence.
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TIMESTAMPS:
00:00 A new Superpower in the making.
00:46 A Brain-Scale Supercomputer?
02:47 China Tech vs USA Tech.
05:30 Chinese Semiconductor Technology.
07:39 Last Words.
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#china #computing #usa

Officials and engineers at Kawasaki have unveiled Bex, a quadruped robot that can walk, roll around and even carry a human passenger on its back—at this year’s 2022 International Robot Exhibition in Tokyo. At the exhibition, Bex was configured to look like an Ibex, a type of wild goat, which is where it gets its name.

Bex was created as part of an effort at Kawasaki the company calls a “robust humanoid platform” with a project called Kaleido. Most such efforts from the project have involved robots that are halfway between human-like robots and wheeled bots. Bex appears to be an aberration—it is a quadruped with wheels on its knees. The robot can walk around, similar in many respects to a quadruped from Boston Dynamics, though much slower. But it also squats down to its knees, locks its joints and fires up a motor that drives the robot around like a car. Bex can also carry cargo (up to 100 kilograms) such as crops or humans. At the exhibition, Bex was mounted by an engineer and ridden in circles like a pony. The team at Kawasaki has also made the robot a little glitzier than many of its competitors—it has flashing lights that run up and down its neck and antlers.

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The first Australian-produced military combat aircraft in over half a century.

Boeing’s Loyal Wingman is now officially the “MQ-28A Ghost Bat.” The new military designator and name that will be used by the Royal Australian Air Force (RAAF) for the autonomous combat drone was announced during a ceremony at the Amberley Royal Australian Air Force Base in Queensland today.

Giving the Loyal Wingman an official name may seem trivial, but it represents two major steps for the program. Being named after a native Australian bat, it acknowledges the first Australian-produced military combat aircraft in over half a century, and it also shows that the drone is moving out of the experimental phase and into a path for full deployment with the RAAF and sales to international customers.

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Let’s look at some of the best emerging technologies!

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A deep neural network could help classicists restore incomplete inscriptions from ancient times — and reveal new works of literature.