Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

Recent advances in machine learning have opened transformative avenues for investigating complex problems in string theory and geometry. By integrating sophisticated algorithms with theoretical ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

MIT researchers have developed a technique to identify and remove specific data points in training datasets that disproportionately contribute to a model's errors on minority subgroups. This approach ...

ML tailors banking solutions by analyzing transactions, spending habits, and financial goals. It detects fraud in real time, adapts to threats, and verifies customer identity behaviorally. AI chatbots ...

Transfer learning reuses existing ML models for new tasks, speeding up development and enhancing performance. It reduces data requirements for training ML models on new tasks, facilitating quicker ...

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Machine learning and deep learning are both parts of artificial intelligence, but they work in different ways — like a smart student versus a super-specialised ...