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Scientists advance quantum signaling with twisted light technology

A tiny device that entangles light and electrons without super-cooling could revolutionize quantum tech in cryptography, computing, and AI.

Present-day quantum computers are big, expensive, and impractical, operating at temperatures near-459 degrees Fahrenheit, or “absolute zero.” In a new paper, however, materials scientists at Stanford University introduce a new nanoscale optical device that works at room temperature to entangle the spin of photons (particles of light) and electrons to achieve quantum communication—an approach that uses the laws of quantum physics to transmit and process data. The technology could usher in a new era of low-cost, low-energy quantum components able to communicate over great distances.

“The material in question is not really new, but the way we use it is,” says Jennifer Dionne, a professor of materials science and engineering and senior author of the paper just published in Nature Communications describing the novel device. “It provides a very versatile, stable spin connection between electrons and photons that is the theoretical basis of quantum communication. Typically, however, the electrons lose their spin too quickly to be useful.”

ChatGPT is down worldwide, conversations dissapeared for users

OpenAI’s AI-powered ChatGPT is down worldwide with users receiving errors when attempting to access chats, with no reasons currently given.

If you are affected, you will see errors, “something seems to have gone wrong,” errors, with ChatGPT adding that “There was an error generating a response” to their queries.

In our tests, BleepingComputer observed that GPT keeps loading, and the response never comes.

Why Doesn’t Anyone Monitor AI Consciousness?

Go to https://ground.news/sabine to get 40% off the Vantage plan and see through sensationalized reporting. Stay fully informed on events around the world with Ground News.

AI is changing the world – how we work, how we write, and how we consume media. But it doesn’t seem like many people are interested in how AI is learning to think about itself. I am convinced that eventually AI will become conscious and I am beginning to worry that we simply wouldn’t notice because no one is watching out for it.

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A rhythmically pulsing leaf-spring DNA-origami nanoengine that drives a passive follower

DNA nano machine year 2023.


An autonomous DNA-origami nanomachine powered by the chemical energy of DNA-templated RNA-transcription-consuming nucleoside triphosphates as fuel performs rhythmic pulsations is demonstrated. In combination with a passive follower, the nanomachine acts as a mechanical driver with molecular precision.

Physicists overcome fundamental limitation of acoustic levitation

Using sound to get objects to float works well if a single particle is levitated, but it causes multiple particles to collapse into a clump in mid-air. Physicists at the Institute of Science and Technology Austria (ISTA) have now found a way to keep them apart using charge. Their findings, published in Proceedings of the National Academy of Sciences, could find applications in materials science, robotics, and microengineering.

Who hasn’t dreamed of overcoming gravity and getting objects to hover above ground?

In 2013, Scott Waitukaitis, now an assistant professor at the Institute of Science and Technology Austria (ISTA), became interested in using acoustic levitation as a tool to study various physical phenomena. At that time, only a handful of research groups were using this technique for similar purposes.

AI that sees and speaks

Naoufel werghi, professor of computer science at the centre for cyber-physical systems, khalifa university.

Naoufel Werghi aims not only to replicate the human visual system, but to extend its capabilities so that machines can perceive patterns invisible to the eye and process information at scales beyond human capacity.

I started my PhD working on robots that can ‘see’—machines capable of sensing the environment, analyzing images and making decisions. As I delved deeper, I realized that I was grappling with the same fundamental problems that once preoccupied David Marr, a visionary neuroscientist and the founder of modern computer vision. He believed that for robots to see, we first needed computers to analyze images and understand the context.

Digital twins for in vivo metabolic flux estimations in patients with brain cancer

Quantifying metabolic activity in patient tumors could advance personalized cancer targeting. Meghdadi et al. develop a digital twin framework using machine learning to quantify metabolic fluxes in tissues from patients with glioma, identifying which patients may benefit from different targeted metabolic therapies like specialized diets or pharmacologic agents.

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