Science

A new system offers a scalable way to analyze historical time-series data, enabling deeper insights and cost optimization for operational analytics.

New research demonstrates how incorporating real-world factors into machine learning models dramatically improves the accuracy of demand forecasting for optimized inventory control.

New research demonstrates that existing deep learning models, refined with improved data handling, can effectively classify radio galaxies without the need for complex new architectures.

A new analysis reveals a predictable pattern in how artificial intelligence generates text, offering a robust method for distinguishing it from human writing.

A new cognitive agent, Mind2Report, aims to synthesize commercial-grade reports with minimal human intervention, marking a significant step toward fully automated research capabilities.

New research moves beyond simply observing transformer behavior to identify which attention heads are causally responsible for specific functionalities.

A new study reveals that artificial intelligence, specifically deep reinforcement learning, is consistently delivering superior results in navigating complex financial markets.

Researchers have launched a live, multi-agent system to rigorously evaluate the performance of artificial intelligence in real-world financial forecasting scenarios.

A novel model combining Neural Prophet and deep neural networks demonstrates improved accuracy in forecasting stock market prices.

A new framework combines the power of generative adversarial networks with logical reasoning to create more consistent and structurally sound generated content.