Summary: Ink authentication is often complicated by tampering, aging, and chemical variability. Now, forensic scientists are ...

To assess predictive potential, the researchers applied machine learning models—including gradient-boosted decision trees and ...

This research aims to reactivate object-oriented databases using intelligent tools to improve performance and accuracy in ...

Let's say you're reading a story, or playing a game of chess. You may not have noticed, but each step of the way, your mind ...

Apart from simple diagnosis, the study takes an important step toward predictive health monitoring by modeling the risk of ...

In today's AI-driven world, AI tools for data analysis have supercharged the ability to extract meaningful insights from vast ...

Seattle City Light underwent a shift to data-driven utility vegetation management to manage risks and improve reliability.

KAIST (President Kwang Hyung Lee) announced on the 20th that a research team led by Professor Sungjin Ahn in the School of Computing has developed a new technology that significantly improves the ...

Diffusion models are widely used in many AI applications, but research on efficient inference-time scalability, particularly for reasoning and planning (known as System 2 abilities) has been lacking.

Structured maturity models can address program, reliability and safety improvements while ensuring regulatory compliance.

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

In a move that could reshape how enterprises deploy AI, Japanese research lab Sakana AI has introduced TreeQuest, an open-source framework built on a novel technique that allows multiple large ...