In several Tennessee high school classrooms, computer science students are stepping away from their screens. Instead, as part of a learning tool ...
Explore how core mathematical concepts like linear algebra, probability, and optimization drive AI, revealing its pattern-recognition capabilities.
A new deep learning algorithm can detect vehicles linked to illicit activity, including the movement of nuclear materials. The software can identify unusual vehicle patterns by analysing drone, camera ...
There's an iconic scene at the end of the 1985 film "Back to the Future" when Doc Brown returns from 2015 to warn Marty McFly and his future wife, Jennifer, that their future children have "problems." ...
Breaking Traditional Encryption Protocols: Quantum Computing and the Future of Secure Communications
Introduction Envision our digital world as a sprawling universe filled with glittering constellations of encrypted data, each packet of information ...
The truth is that even the most optimistic vendor estimates for this would put very nascent stages of enterprise value toward ...
In the context of strong digital technology development, the boundaries of workspace are gradually being blurred. No longer confined within four office walls, more and more people can work remotely ...
In “A World Appears,” Michael Pollan dives headfirst into the mystery. Why does it feel like something to be you ...
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'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images
Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.
A new report finds that of 154 specific claims about how AI will benefit the climate, just a quarter cited academic research.
How can we achieve a balance between the growing energy demands of AI and its potential contributions to achieving the energy transition?
Researchers at College of Food, Agricultural and Natural Resource Sciences are using AI to detect patterns across landscapes, atmospheres and ecosystems at scales that were previously impossible.
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