A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

PolyRL is an open-source framework for reinforcement learning-based molecular generation, designed to accelerate the discovery of polymeric membranes for CO₂/N₂ gas separation. It integrates multiple ...

Explore the hidden trade-offs of reinforcement learning in AI and why base models might hold the key to true intelligence.

This system utilizes machine learning algorithms to optimize the operation of particle accelerators, reducing manual intervention and enhancing precision in real-time control.

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in ...

DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a preliminary step, demonstrates remarkable reasoning capabilities. Through RL, ...

The study illustrates how reinforcement learning can facilitate the transition from conceptual design to implementation by automating optimization processes, enabling interface automation, and ...