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Category: robotics/AI – Page 1,549

An artificial intelligence invents 40,000 chemical weapons in just 6 hours

A.I. is only beginning to show what it can do for modern medicine.

In today’s society, artificial intelligence (A.I.) is mostly used for good. But what if it was not?

Naive thinking “The thought had never previously struck us. We were vaguely aware of security concerns around work with pathogens or toxic chemicals, but that did not relate to us; we primarily operate in a virtual setting. Our work is rooted in building machine learning models for therapeutic and toxic targets to better assist in the design of new molecules for drug discovery,” wrote the researchers in their paper. “We have spent decades using computers and A.I. to improve human health—not to degrade it. We were naive in thinking about the potential misuse of our trade, as our aim had always been to avoid molecular features that could interfere with the many different classes of proteins essential to human life.”

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Researchers from Collaborations Pharmaceuticals tweaked artificial intelligence to look for chemical weapons, and impressively enough the machine learning algorithm found 40,000 options in just six hours.

Using electron microscopy and automatic atom-tracking to learn more about grain boundaries in metals during deformation

A team of researchers affiliated with multiple institutions in China and the U.S. has found that it is possible to track the sliding of grain boundaries in some metals at the atomic scale using an electron microscope and an automatic atom tracker. In their paper published in the journal Science, the group describes their study of platinum using their new technique and the discovery they made in doing so.

Scientists have been studying the properties of metals for many years. Learning more about how crystal grains in certain metals interact with one another has led to the development of new kinds of metals and applications for their use. In their recent effort, the researchers took a novel approach to studying the sliding that occurs between grains and in so doing have learned something new.

When crystalline metals are deformed, the grains that they are made of move against one another, and the way they move determines many of their properties, such as malleability. To learn more about what happens between grains in such metals during deformity, the researchers used two types of technologies: and automated atom-tracking.

Gensyn applies a token to distributed computing for AI developers, raises $6.5M

For self-driving cars and other applications developed using AI, you need what’s known as “deep learning”, the core concepts of which emerged in the ’50s. This requires training models based on similar patterns as seen in the human brain. This, in turn, requires a large amount of compute power, as afforded by TPUs (tensor processing units) or GPUs (graphics processing units) running for lengthy periods. However, cost of this compute power is out of reach of most AI developers, who largely rent it from cloud computing platforms such as AWS or Azure. What is to be done?

Well, one approach is that taken by U.K. startup Gensyn. It’s taken the idea of the distributed computing power of older projects such as SETI@home and the COVID-19 focussed Folding@home and applied it in the direction of this desire for deep learning amongst AI developers. The result is a way to get high-performance compute power from a distributed network of computers.

Gensyn has now raised a $6.5 million seed led by Eden Block, a web3 VC. Also participating in the round is Galaxy Digital, Maven 11, Coinfund, Hypersphere, Zee Prime and founders from some blockchain protocols. This adds to a previously unannounced pre-seed investment of $1.1 millionin 2021 — led by 7percent Ventures and Counterview Capital, with participation from Entrepreneur First and id4 Ventures.

MIT researchers use simulation to train a robot to run at high speeds

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.

Researchers Perform Largest Quantum Computing Chemistry Simulations to Date

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.

This Insane Chinese Supercomputer Changes EVERYTHING

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

Bex: A walking, rolling quadruped robot that can carry a person around

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 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 , Bex was mounted by an 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.

Officials with Kawasaki noted at the show that the robot’s head can be replaced with other suitable alternatives such as a horse’s head or even nothing at all. They also noted that Bex has been engineered to move quickly in its wheeled configuration and that the walking configuration is to deal with uneven terrain. Also, the team put stability at the forefront. When the robot is rolling, all of its wheels are always on the ground, and when it is walking, its gait keeps at least two feet on the ground. This reduced computation requirements and made the robot safer to use around humans.

Boeing’s Loyal Wingman drone is now officially the MQ-28A Ghost Bat

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.

Taking only three years from the first design to first flight, the Ghost Bat’s rapid development owes much to Boeing Australia’s use of digital engineering and advanced manufacturing techniques. When in service, the autonomous combat craft will have the performance and range comparable to that of a conventional fighter aircraft. This will allow it to carry out single missions and team with other crewed or uncrewed aircraft.