Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

The growth and impact of artificial intelligence are limited by the power and energy that it takes to train machine learning ...

Researchers say that the recommendation algorithm published by X doesn't offer the kind of transparency that would actually ...

Discover how price efficiency reflects available information in market prices, explore examples, and understand its limitations within financial markets.

Long sales cycles, low conversion volume, and multi-stage purchase journeys make measurement and attribution harder, creating real obstacles to campaign optimization. For B2Bs and brands selling ...

Even as the U.S. economy adds jobs, there are fewer entry-level positions for college graduates just entering the labor market. "For the first time in modern history, a bachelor's degree is no longer ...

Amazon said Tuesday that it plans to cut 14,000 corporate jobs, its biggest round of layoffs in years, as it invests more in artificial intelligence. In Amazon’s announcement, top human resources ...

MIAMI – Observations and other notes of interest from Sunday night’s 115-107 victory over the New York Knicks: – This Jaime Jaquez Jr. thing is real. – Cast one moment Sunday at power forward. – ...

From powering search engines to securing data and optimizing networks, algorithms underpin nearly every aspect of modern technology. Understanding how efficiently they can solve problems — and where ...

Co-authored by Nigel Bairstow, Ph.D., and Meezab Fatima Khan, Research Assistant Artificial intelligence has quietly reshaped the way we shop, listen to music, and even decide what to eat for dinner.

Abstract: Most of the approaches proposed so far to craft targeted adversarial examples against Deep Learning classifiers are highly suboptimal and typically rely on increasing the likelihood of the ...