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Category: information science – Page 16

Modern AI systems have fulfilled Turing’s vision of machines that learn and converse like humans, but challenges remain. A new paper highlights concerns about energy consumption and societal inequality while calling for more robust AI testing to ensure ethical and sustainable progress.

A perspective published on November 13 in Intelligent Computing, a Science Partner Journal, argues that modern artificial intelligence.

Artificial Intelligence (AI) is a branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. These tasks include understanding natural language, recognizing patterns, solving problems, and learning from experience. AI technologies use algorithms and massive amounts of data to train models that can make decisions, automate processes, and improve over time through machine learning. The applications of AI are diverse, impacting fields such as healthcare, finance, automotive, and entertainment, fundamentally changing the way we interact with technology.

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The intricate relationship between quantum mechanics and classical physics has long puzzled scientists. Quantum mechanics operates in a bizarre world where particles can exist in multiple states simultaneously, a concept known as superposition. However, this principle appears to break down in the macroscopic realm.

Planets, stars, and even the universe itself don’t exhibit such superpositions, creating a significant challenge in understanding how the universe transitions from quantum to classical behavior.

At the heart of this enigma is the question: how does the universe, if fundamentally quantum, adhere to classical laws like general relativity? This puzzle has led to groundbreaking work by researchers such as Matteo Carlesso and his colleagues at the University of Trieste.

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Dive into the mesmerizing world of quantum mechanics and uncover the secrets of the quantum vacuum—a concept that challenges everything we thought we knew about empty space. This video explores the dynamic, energy-filled realm of the quantum vacuum, where virtual particles pop in and out of existence and Zero Point Energy offers tantalizing possibilities for clean, limitless power.

Learn about the Casimir Effect, a fascinating phenomenon where quantum fluctuations create forces between metal plates, and discover how these principles could revolutionize fields like nanotechnology, energy production, and even space exploration. From the Heisenberg Uncertainty Principle to the Reverse Casimir Effect, this journey into quantum mechanics highlights the incredible potential of harnessing Zero Point Energy for a sustainable future.

Whether you’re a science enthusiast, a technology visionary, or just curious about the universe’s mysteries, this video will inspire you with the groundbreaking implications of the quantum vacuum and Zero Point Energy.

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A breakthrough in artificial intelligence.

Artificial Intelligence (AI) is a branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. These tasks include understanding natural language, recognizing patterns, solving problems, and learning from experience. AI technologies use algorithms and massive amounts of data to train models that can make decisions, automate processes, and improve over time through machine learning. The applications of AI are diverse, impacting fields such as healthcare, finance, automotive, and entertainment, fundamentally changing the way we interact with technology.

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Simulations of neutron stars provide new bounds on their properties, such as their internal pressure and their maximum mass.

Studying neutron stars is tricky. The nearest one is about 400 light-years away, so sending a probe would likely take half a million years with current space-faring technology. Telescopes don’t reveal much detail from our vantage point, since neutron stars are only the size of a small city and thus appear as mere points in the sky. And no laboratory on Earth can reproduce the inside of neutron stars, because their density is too great, being several times that of atomic nuclei. That high density also poses a problem for theory, as the equations for neutron-star matter cannot be solved with standard computational techniques. But these difficulties have not stopped efforts to understand these mysterious objects. Using a combination of theory-based methods and computer simulations, Ryan Abbott from MIT and colleagues have obtained new, rigorous constraints for the properties of the interior of neutron stars [1].

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Quantum physics is a very diverse field: it describes particle collisions shortly after the Big Bang as well as electrons in solid materials or atoms far out in space. But not all quantum objects are equally easy to study. For some—such as the early universe—direct experiments are not possible at all.

However, in many cases, quantum simulators can be used instead: one quantum system (for example, a cloud of ultracold atoms) is studied in order to learn something about another system that looks physically very different, but still follows the same laws, i.e. adheres to the same mathematical equations.

It is often difficult to find out which equations determine a particular quantum system. Normally, one first has to make theoretical assumptions and then conduct experiments to check whether these assumptions prove correct.

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