Superconductors sit at the heart of some of the most ambitious technologies on the horizon, from lossless power grids to ...

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

“Prompt injection, much like scams and social engineering on the web, is unlikely to ever be fully ‘solved,'” OpenAI wrote in ...

Reinforcement Learning, Explainable AI, Computational Psychiatry, Antidepressant Dose Optimization, Major Depressive Disorder, Treatment Personalization, Clinical Decision Support Share and Cite: de ...

Step inside the Soft Robotics Lab at ETH Zurich, and you find yourself in a space that is part children's nursery, part ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a specific approach to reach the same goal.

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...

Abstract: In the domain of continuous control, deep reinforcement learning (DRL) demonstrates promising results. However, the dependence of DRL on deep neural networks (DNNs) results in the demand for ...

In a college-entrance-exam landscape long dominated by the SAT and the ACT, a relative newcomer has started to gain traction—especially in red states. The Classic Learning Test, first unveiled a ...