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A new algorithm that fast forwards simulations could bring greater use ability to current and near-term quantum computers, opening the way for applications to run past strict time limits that hamper many quantum calculations.

“Quantum computers have a limited time to perform calculations before their useful quantum nature, which we call coherence, breaks down,” said Andrew Sornborger of the Computer, Computational, and Statistical Sciences division at Los Alamos National Laboratory, and senior author on a paper announcing the research. “With a we have developed and tested, we will be able to fast forward quantum simulations to solve problems that were previously out of reach.”

Computers built of quantum components, known as qubits, can potentially solve extremely difficult problems that exceed the capabilities of even the most powerful modern supercomputers. Applications include faster analysis of large data sets, , and unraveling the mysteries of superconductivity, to name a few of the possibilities that could lead to major technological and scientific breakthroughs in the near future.

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Autonomous tractors for farming.

OSAKA — Kubota has partnered with U.S. chipmaker Nvidia to develop highly sophisticated self-driving farm tractors, the Japanese machinery maker said Tuesday.

The tractors will be equipped with Nvidia graphics processing units and artificial intelligence, coupled with cameras to instantly process collected data.

The farming technology is expected to provide a labor-saving solution that will help address the shortage of workers in Japan’s agricultural industry.

Continue reading “Kubota taps Nvidia tech for smart-farming autonomous tractors” | >

With artificial intelligence (AI) tools and machine learning algorithms now making their way into a wide variety of settings, assessing their security and ensuring that they are protected against cyberattacks is of utmost importance. As most AI algorithms and models are trained on large online datasets and third-party databases, they are vulnerable to a variety of attacks, including neural Trojan attacks.

A neural Trojan attack occurs when an attacker inserts what is known as a hidden Trojan trigger or backdoor inside an AI model during its training. This trigger allows the attacker to hijack the model’s prediction at a later stage, causing it to classify data incorrectly. Detecting these attacks and mitigating their impact can be very challenging, as a targeted model typically performs well and in alignment with a developer’s expectations until the Trojan backdoor is activated.

Researchers at University of California, San Diego have recently created CLEANN, an end-to-end framework designed to protect embedded from Trojan attacks. This framework, presented in a paper pre-published on arXiv and set to be presented at the 2020 IEEE/ACM International Conference on Computer-Aided Design, was found to perform better than previously developed Trojan shields and detection methods.

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Einstein’s theory of special relativity gave us the speed limit of the Universe — that of light in a vacuum. But the absolute top speed of sound, through any medium, has been somewhat trickier to constrain.

It’s impossible to measure the speed of sound in every single material in existence, but scientists have now managed to pin down an upper limit based on fundamental constants, the universal parameters by which we understand the physics of the Universe.

That speed limit, according to the new calculations, is 36 kilometres per second (22 miles per second). That’s about twice the speed of sound travelling through diamond.

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