Science

Researchers are leveraging the power of large language models, guided by market regime awareness, to achieve more accurate predictions of financial volatility.

Combining pre-trained language models is rapidly becoming a powerful technique for building more capable, aligned, and efficient artificial intelligence systems.

New research reveals that successful artificial intelligence adoption in SMEs hinges on building internal capabilities and leveraging external ecosystems, rather than simply implementing technology.

A new approach leverages autonomous AI systems to automate and optimize federated learning across 6G networks, paving the way for more scalable and adaptable distributed intelligence.

A new study reveals how artificial intelligence can automatically identify patients eligible for critical cardiovascular risk management based on their complete medical history.

New research reveals a surprising connection between the weight matrices of trained neural networks and the dynamics of financial portfolios.

Researchers have created a publicly available dataset and evaluation framework to assess how well natural language processing and retrieval-augmented generation systems align with the requirements of the EU AI Act.

New research explores how large language models assess investor profiles, revealing both promise and pitfalls in using AI for personalized financial advice.

New research shows that analyzing the emotional tone of news articles, using advanced AI, can significantly improve the accuracy of aluminum price forecasting.

A new data-driven approach leveraging machine learning and combined data sources offers unprecedented accuracy in forecasting spatial spectrum demand.