Science

A new review charts the rapidly evolving global landscape of artificial intelligence governance, offering critical insights for organizations seeking to comply with emerging rules.

A new approach links generative AI outputs to their training data, offering insights into stylistic influences and potential copyright concerns.

A new benchmark assesses how well artificial intelligence agents can handle real-world financial tasks, revealing key limitations and pathways to improvement.

A new open-source large language model, DeepSeek-V3.2, is closing the performance gap with proprietary systems through innovations in model architecture and training techniques.

A new framework reveals that artificial intelligence-powered trading agents are surprisingly vulnerable to manipulation, potentially jeopardizing investment portfolios.

New research reveals how market turbulence can unexpectedly encourage price-fixing behavior in artificial intelligence-driven pricing systems.

This research investigates the potential of deep learning techniques to identify and profit from temporary mispricings within the Polish equities market.

A new study explores how combining the strengths of deep learning and traditional machine learning can refine stock market forecasts.

A new framework is emerging that moves beyond traditional algorithmic trading to create fully autonomous, language-driven agents capable of navigating complex financial markets.

New research demonstrates how artificial intelligence can analyze prediction markets to uncover relationships between different contracts, potentially leading to better forecasts and trading strategies.