Science

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.

Researchers have developed a novel approach to reliably detect manipulated regions within images generated by inpainting algorithms, bolstering trust in visual content.

A new reinforcement learning approach allows large language models to master complex reasoning tasks simply by observing expert demonstrations.

A new method intelligently reduces the number of tokens processed by Vision Transformers, maintaining performance by prioritizing visually important information.

A new technique embeds robust, undetectable signals within synthetic datasets to verify their origin and integrity.