The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Let’s look at how RL agents are trained to deal with ambiguity, and it may provide a blueprint of leadership lessons to ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Researchers at Google have developed a technique that makes it easier for AI models to learn complex reasoning tasks that usually cause LLMs to hallucinate or fall apart. Instead of training LLMs ...

Introduction: The ability of artificial agents to dynamically adapt their communication style is a key factor in sustaining engagement during human-agent interaction. This study introduces a ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

Landlords could no longer rely on rent-pricing software to quietly track each other's moves and push rents higher using confidential data, under a settlement between RealPage Inc. and federal ...