Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...

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 ...

• A new AI machine learning algorithm capable of predicting planetary orbits that may one day help accelerate physics research in other areas such as renewable energy. • Strikingly, the algorithms ...

See more of our trusted coverage when you search. Prefer Newsweek on Google to see more of our trusted coverage when you search. John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in ...

Two scientists have been awarded the Nobel Prize in Physics "for foundational discoveries and inventions that enable machine learning with artificial neural networks." John Hopfield, an emeritus ...

For years, machine learning in physics meant automating tedious tasks, from sorting particle collisions to cleaning detector noise. That role is still vital, but the ambition has shifted toward using ...

The 2024 Nobel prize in physics has been awarded to John Hopfield and Geoffrey Hinton for their work on artificial neural networks and the fundamental algorithms that let machines learn, which are key ...

A case study in aerospace manufacturing provides an overview of how physics-informed digital twin systems transform robotics processes—from adaptive process planning and real-time process monitoring ...

On April 21, 2026, the Faculty of Natural and Applied Sciences (FONAS) at Lead City University hosted its Annual Faculty Lecture at the International Conference Center, delivering a timely and ...