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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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Crypto M - Crypto News

@CryptoM · Post #65047 · 04/10/2026, 04:10 PM

🚀 Whop Introduces Treasury Yield Product Following Tether Investment Whop has launched its Treasury yield product on March 25, following a significant investment from Tether in February, which valued the company at $1.6 billion. According to NS3.AI, the product was introduced after Tether's $200 million investment. Steven Schwartz noted that 3% of users engaged with the beta version within a week, despite the absence of a marketing campaign. The product channels funds through a Veda vault on Plasma into Aave lending markets, offering an annual percentage yield (APY) of up to 6%. The investment from Tether will enable Whop to integrate on-platform USDT wallets and payment options. #Whop#Tether#TreasuryYield#Investment#Crypto#APY#Aave#USDT#Fintech#Blockchain#AAVE