A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as ...

The Parallel-R1 framework uses reinforcement learning to teach models how to explore multiple reasoning paths at once, ...

A (NRL) research team successfully conducted the first reinforcement learning (RL) control of a free-flyer in space on May 27 ...

New joint safety testing from UK-based nonprofit Apollo Research and OpenAI set out to reduce secretive behaviors like scheming in AI models. What researchers found could complicate promising ...

These days, artificial intelligence developers, investors and founders are all obsessed with “reinforcement learning,” a ...

Abstract: The global shift toward distributed energy resources (DERs) has accelerated the deployment of microgrids (MGs), introducing unprecedented control challenges that traditional strategies often ...

K2 Think compares well with reasoning models from OpenAI and DeepSeek but is smaller and more efficient, say researchers ...

Abstract: Temporal difference (TD) learning is a fundamental technique in reinforcement learning that updates value function estimates for states or state-action pairs using a TD target. This target ...

This is Part 2 of a five-part blog series exploring the nature of cognition and its relationship with consciousness. In Part 1, we considered the surprisingly elusive definition of cognition as well ...

The bird has never gotten much credit for being intelligent. But the reinforcement learning powering the world’s most advanced AI systems is far more pigeon than human. In 1943, while the world’s ...