Science

A new deep learning framework leverages the power of attention mechanisms to more accurately forecast equipment failure and remaining useful life.

Researchers have developed a novel method for accurately predicting short-term brain activity using fMRI data, offering improved insights into neural dynamics.

New research examines the impact of large-scale investment on the accuracy and fairness of prediction markets, revealing potential benefits alongside uneven distribution of gains.

Researchers propose a proactive approach to AI safety, shifting focus from reactive testing to identifying inherent risks within an AI’s reasoning structure.

A growing body of evidence suggests that the societal harms caused by artificial intelligence aren’t necessarily due to malicious intent, but rather a fundamental disconnect between what algorithms are designed to achieve and what genuinely benefits human well-being.

A new framework leverages generative AI to anticipate disruptions and proactively adapt supply chain strategies for long-term stability.

Researchers have developed an advanced machine learning system to better forecast the connection between solar flares and coronal mass ejections, crucial events impacting space weather.

Researchers have developed a new method for rigorously evaluating how well large language models can handle multi-step financial tasks by strategically using external tools.

Recent advances in machine learning are offering unprecedented tools for predicting and understanding the complex behavior of chaotic systems.

A new approach directly translates the relational knowledge embedded in language models into graph structures, enhancing predictions of financial market behavior.