A Grand Unified Theory of Artificial Intelligence

In the 1950s and '60s, artificial-intelligence researchers saw themselves as trying to uncover the rules of thought. But those rules turned out to be way more complicated than anyone had imagined. Since then, artificial-intelligence ...

Unlocking the full potential of Auger electron spectroscopy

Auger electron spectroscopy (AES) is an incredibly useful technique for probing material samples—but current assumptions about the process ignore some of the key time-dependent effects it involves. So far, this has resulted ...

AI model directly compares properties of potential new drugs

Biomedical engineers at Duke University have developed an AI platform that autonomously compares molecules and learns from their variations to anticipate property differences critical to discovering new pharmaceuticals. The ...

A 'gold standard' for computational materials science codes

For the past few decades, physicists and materials scientists around the world have been busy developing computer codes that simulate the key properties of materials, and they can now choose from a whole family of such tools, ...

Exploring parameter shift for quantum Fisher information

In a recent publication in EPJ Quantum Technology, Le Bin Ho from Tohoku University's Frontier Institute for Interdisciplinary Sciences has developed a technique called time-dependent stochastic parameter shift in the realm ...

Guiding the design of silicon devices with improved efficiency

Silicon is one of the most pervasive functional materials of the modern age, underpinning semiconductor technologies ranging from microelectronics to solar cells. Indeed, silicon transistors enable computing applications ...

How AI might speed up the discovery of new drugs

Artificial intelligence can generate poems and essays, create responsive game characters, analyze vast amounts of data and detect patterns that the human eye might miss. Imagine what AI could do for drug discovery, traditionally ...

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