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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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Venture Village Wall 🦄

@venturevillagewall · Post #4266 · 02/28/2025, 07:00 AM

AI Predictions: From Vacuums to Real Impact AI-powered prediction platforms are gaining traction, with a focus on forecasting reactions based on content and audience. Initial predictions using tools like ChatGPT yield 17% accuracy, but considering audience interactions can boost accuracy to 83%. This innovative approach helped a startup refine its pitch to enter Y Combinator. Discover more insights on enhancing prediction accuracy in various fields here. #AI#Startup#Prediction#YCombinator#Marketing#Innovation#Tech#Growth#Entrepreneurship#Forecasting#AudienceAnalysis#DataScience#MachineLearning#Success#Business#Trends#Platforms#Metrics#Investment#VC