By explicitly modeling each step of a problem and gradually fading away supports, teachers can give students a clear path to mastering new content.

As AI tools evolve at a rapid pace, smaller, more flexible learning environments are well-positioned to test new approaches, develop expectations, and adjust as needed.

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...

Abstract: Servo control systems exhibit strong coupling among multiple control parameters, posing dual challenges of efficiency and stability during optimization. Traditional parameter tuning ...

Abstract: Recent advances in data-driven methods have significantly improved battery capacity estimation, yet most existing approaches remain constrained by their reliance on supervised learning, ...