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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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@abmedia_news · Post #23991 · 04/20/2026, 03:37 AM

【🔗 DeFi|新加坡 Cobo 推出 Agentic Wallet:AI 代理可自主上鏈執行,結合 MPC 分層簽核與 Pact 約定機制】 Cobo 於 4/19 推出 Agentic Wallet,MPC 架構下 AI 代理執行任務需先取得 Pact 四層授權(意圖、計畫、政策、完成條件),高額動作要 Human+Cobo 共簽,任何單方都無法動資。 #Cobo#AgenticWallet#MPC 📍閱讀全文: https://abmedia.io/cobo-agentic-wallet-singapore-ai-agent-mpc-onchain-execution