5 links tagged with all of: open-source + reinforcement-learning + ai
Click any tag below to further narrow down your results
Links
INTELLECT-3 is a Mixture-of-Experts model with over 100 billion parameters, trained using a custom reinforcement learning framework. It outperforms larger models across various benchmarks in math, code, and reasoning. The training infrastructure and datasets are open-sourced for public use and research.
NitroGen is an open-source model designed for creating gaming agents that can learn from internet videos. It takes pixel input from games and predicts gamepad actions but currently has limitations, such as only processing the last frame and lacking long-term planning abilities. Users must provide their own game copies to run the model on Windows.
INTELLECT-2 is a groundbreaking 32 billion parameter model trained using a decentralized reinforcement learning framework called PRIME-RL, enabling fully asynchronous training across a global network of contributors. The model demonstrates significant improvements in reasoning tasks and is open-sourced to foster further research in decentralized AI training methodologies.
OpenThinkIMG is an open-source framework that enables Large Vision-Language Models (LVLMs) to engage in interactive visual cognition, allowing AI agents to effectively think with images. It features a flexible tool management system, a dynamic inference pipeline, and a novel reinforcement learning approach called V-ToolRL, which enhances the adaptability and performance of visual reasoning tasks. The project aims to bridge the gap between human-like visual cognition and AI capabilities by providing a standardized platform for tool-augmented reasoning.
The Environments Hub is being launched as an open, community-driven platform for reinforcement learning (RL) environments, aiming to provide a shared space for researchers and developers to build, share, and utilize these environments effectively. This initiative seeks to democratize access to high-quality RL tools, fostering innovation in AI by lowering barriers to creating and training models, while also promoting open-source development in contrast to proprietary systems used by large labs.