A surprisingly easy way to multiply an AI model’s profit is to drive decisions via expected value instead of predictive scores. Here's how, illustrated with fraud detection.

RIT computer science professor Weijie Zhao has earned a National Science Foundation CAREER Award to defend machine learning ...

Read more about Quantum machine learning shows promise for adaptive learning, but classrooms are not ready on Devdiscourse ...

Introduction The creator economy has blossomed into a $250 billion industry, and AI is rapidly dominating as the major driver ...

The Rocklin Lab at Northwestern University today announced the release of the MGnify Stability Dataset, a large-scale experimental resource containing folding stability measurements for 1.8 million ...

From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has ...

When Daniel Haders, Ph.D., was working in venture capital, he was on the hunt for an AI-driven drug discovery company that ...

For more than a decade, a fundamental mystery has surrounded graphene—the one-atom-thick “wonder material” known for its ...

When you tap your card, a signal travels to your bank’s fraud detection system in the time it takes to blink. The transaction processing at your checkout is fully automated, ope ...

The transformation commonly called the digital revolution did not begin with dazzling apps or sleek devices, but with a ...

Driving into San Francisco from the airport recently, I passed a billboard that said, “Welcome to AI country. Population: Everyone.” That seemed to capture things well. The next day, I was at the ...

A team spends months - sometimes over a year - building an AI system. Engineers are hired, infrastructure is set up, a model ...