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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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MessageInABottle

@mib_messageinabottle · Post #6953 · 05/26/2024, 12:59 PM

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🇬🇧#UK #PreCrime "I WAS MISIDENTIFIED AS SHOPLIFTER BY FACIAL RECOGNITION TECH" Sara needed some chocolate - she had had one of those days - so wandered into a #HomeBargains store. "Within less than a minute, I'm approached by a store worker who comes up to me and says, 'You're a thief, you need to leave the store'." Sara - who wants to remain anonymous - was wrongly accused after being flagged by a facial-recognition system called #Facewatch. She says after her bag was searched she was led out of the shop, and told she was banned from all stores using the technology. Facewatch later wrote to Sara and acknowledged it had made an error. The #MetropolitanPolice in #London say that around one in every 33,000 people who walk by its cameras is misidentified. But the error count is much higher once someone is actually flagged. One in 40 alerts so far this year has been a false positive #AI #FacialRecognition

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