The fields of psychology, robotics and machine learning have each been using some version of the concept for decades. You likely have a world model running inside your skull right now — it’s how you ...

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 ...

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 ...

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

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

Neural networks aren’t the only game in artificial intelligence, but you’d be forgiven for thinking otherwise after the hot streak sparked by ChatGPT’s arrival in 2022. That model’s ...

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 ...

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

The idea of thinking machines (Turing, 1950) and the term “artificial intelligence” were introduced in the 1950s (McCarthy, 2007). The 1960s and 1970s saw the development of neural networks. The 1980s ...