A new approach leverages graph neural networks and attention mechanisms to not only identify threats in industrial control systems, but also to explain why they’re happening.
A new machine learning model significantly improves the accuracy of static analysis by predicting and filtering out false positives in vulnerability reports.
A new framework leverages the power of artificial intelligence to automate and improve the accuracy and adaptability of environmental, social, and governance reporting.
A new approach harnesses the underlying dynamics of chaotic systems to significantly improve long-term predictions of extreme events.
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.