A new digital system allows operations on a chip to run in parallel, so an AI program can arrive at the best possible answer ...

The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

Software engineer Sai Bhargav Yalamanchi notes that mathematical tools helping practitioners interpret uncertainty have ...

Trust has always been the foundation of banking. But as artificial intelligence becomes increasingly integrated into banking ...

What Is A Probabilistic Model? A probabilistic model is a statistical tool that accounts for randomness or uncertainty when predicting future events. Instead of giving a definitive answer, it ...

Imagine a world where your computer doesn’t just work harder but smarter, tapping into the very chaos that surrounds us. It’s not science fiction—it’s the dawn of probabilistic and thermodynamic ...

WEST LAFAYETTE, Ind. — “You see, nature is unpredictable. How do you expect to predict it with a computer?” said American physicist Richard Feynman before computer scientists at a conference in 1981.

Amelia Pang is a journalist and an editor at EdTech: Focus on Higher Education. Her work has appeared in the New Republic, Mother Jones, and The New York Times Sunday Review, among other publications.

The rise of artificial intelligence (AI) and machine learning (ML) has created a crisis in computing and a significant need for more hardware that is both energy-efficient and scalable. A key step in ...