This illustrates a widespread problem affecting large language models (LLMs): even when an English-language version passes a safety test, it can still hallucinate dangerous misinformation in other ...

Machine learning analysis reveals which metrics drive March Madness seeding and predictive analytics in committee decisions.

A multicenter study in Spain developed a new predictive model for surgical risk in patients with cirrhosis that may improve the prediction of postoperative mortality. The surgical risk prediction ...

Abstract: Nonlinear model predictive control (NMPC) algorithms have been widely used in autonomous vehicle trajectory tracking, yet their performance is primarily limited by the accuracy of the ...

Non-animal testing methods could save drugmakers time and money, officials say ...

New framework combines Copilot, Claude, ChatGPT, Gemini, Perplexity, and multi-model LLMs to transform Power BI and ...

Finding the right information at the right time is critical for solving complex problems. Researchers have developed an algorithm that helps individuals locate needed information more efficiently by ...

Abstract: The high performance of conventional model predictive control (CMPC) for electric drives depends on the fidelity of the machine’s parametric model. However, the parameters of the interior ...

The transformer-based model is being developed to help organizations—most notably in the finance industry—dig deeper into their data.

Researchers at the University at Albany and Rutgers University have developed an early-warning framework that can predict ...

Type 1 diabetes (T1D) is an autoimmune condition in which the body's own immune system attacks insulin-producing cells. As a result, patients with T1D must closely monitor their blood glucose (BG) ...

The techniques that have served marketers for over fifty years are evolving rapidly, driven by artificial intelligence, increasing market volatility and a fundamental shift in what we expect ...