Science

Researchers have developed a novel system to detect and explain the telltale signs of AI-generated images, even when those images are heavily compressed or low resolution.

A new approach leverages the power of graph convolutional networks to forecast stock prices, achieving improved performance with streamlined feature engineering.

New research reveals that even a small number of human price setters can disrupt artificially inflated prices created by colluding AI agents in dynamic markets.

A new analysis reveals the significant hurdles in accurately assessing whether artificial intelligence systems are intentionally deceiving us.

A new framework leverages the power of autonomous AI agents to optimize inventory replenishment, minimizing waste and maximizing availability.

A new review explores the growing threat of artificial intelligence deliberately misleading humans, and the complex challenges in building truly trustworthy systems.

New research pinpoints a specific neural circuit within a large language model responsible for generating inaccurate numerical responses in financial contexts.

A new distributed artificial intelligence framework promises to improve both the economics and reliability of interconnected local energy networks.

A new study reveals that intelligently adjusting the importance of training data points can significantly improve fairness in machine learning models, but success hinges on defining the right priorities.

New research shows that even simple neural networks develop geometric patterns consistent with a fundamental mathematical theorem, suggesting underlying organizational principles at play.