From disaster zones to underground tunnels, robots are increasingly being sent where humans cannot safely go. But many of ...

Reinforcement Learning, Explainable AI, Computational Psychiatry, Antidepressant Dose Optimization, Major Depressive Disorder, Treatment Personalization, Clinical Decision Support Share and Cite: de ...

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

Through a novel combination of machine learning and atomic force microscopy, researchers in China have unveiled the molecular ...

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...

As we look at the landscape, the narrative has changed again. We are no longer just asking models to act. We are seeing a massive return to fundamental scaling laws, the rise of consumer "super apps" ...

Open-weights models are nothing new for Nvidia — most of the company's headcount is composed of software engineers. However, ...

Ai2 updates its Olmo 3 family of models to Olmo 3.1 following additional extended RL training to boost performance.

A new, real threat has been discovered by Anthropic researchers, one that would have widespread implications going ahead, on ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

For years, Big Tech CEOs have touted visions of AI agents that can autonomously use software applications to complete tasks for people. But take today’s consumer AI agents out for a spin, whether it’s ...

Abstract: Reinforcement learning (RL) is an effective machine learning approach that enables artificial intelligence agents to perform complex tasks and make decisions in dynamic situations. Training ...