Neural networks have emerged as versatile computational frameworks that mimic the functionality of biological brains, while time-delay systems capture the essence of processes where responses are ...

The rapid advancement of artificial intelligence (AI) and machine learning systems has increased the demand for new hardware components that could speed up data analysis while consuming less power. As ...

Scientists from Tomsk Polytechnic University, together with their colleagues, analyzed various methods of planning experiments to determine the optimal technological parameters of polymer scaffold ...

These weights are just numbers but open-weights models also come with a map. "In open-weights [models], you get the weights, which are these numbers, and you get how to map those weights into the ...

Graph neural networks (GNNs) are powerful artificial intelligence (AI) models designed for analyzing complex, unstructured graph data.

And it turns out artificial-intelligence systems can do the ... that when certain student models are trained to be like a ...

Wastewater treatment is energy-intensive, with aeration and pumping among the largest cost drivers. The review details how AI ...

Energy and memory: A new neural network paradigm A dynamic energy landscape is at the heart of theorists' new model of memory retrieval Date: May 14, 2025 Source: University of California - Santa ...

Security researchers have devised a technique to alter deep neural network outputs at the inference stage by changing model ...