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Source channel @githubtrending · Post #15340 · Dec 17

#python#gym#gym_environment#reinforcement_learning#reinforcement_learning_agent#reinforcement_learning_environments#rl_environment#rl_training NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior. https://github.com/NVIDIA-NeMo/Gym

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KIUT | Namangan rasmiy

@kiut_nm · Post #5409 · 01/31/2026, 10:29 AM

🇺🇸🤝🇺🇿 At the initiative of the Vice-Rector for International Cooperation of Kimyo International University in Tashkent, Mr. Rod Clark, an event was held in cooperation with representatives of the U.S. organization OSAC, focusing on one of the issues that is becoming increasingly relevant today — artificial intelligence and cybersecurity. The event brought together representatives of various U.S. companies and organizations operating in Tashkent, who shared their practical experience in implementing modern technologies, ensuring digital security, and current developments in these fields. 🇺🇿🇬🇧🇷🇺: www.kiut.uz #KIUT #OSAC #ArtificialIntelligence