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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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Libreware

@libreware · Post #1262 · 03/28/2024, 03:59 PM

#Bluetooth#vulnerability allows unauthorized user to record & play audio on Bluetooth speaker via #BlueSpy Prevention section explains how you can check if your Bluetooth LE speakers/headsets are vulnerable to this attack using nRF Connect app https://www.mobile-hacker.com/2024/03/22/bluetooth-vulnerability-allows-unauthorized-user-to-record-and-play-audio-on-bluetooth-speakers/ #BlueDucky automates exploitation of Bluetooth pairing vulnerability that leads to 0-click code execution ▪️automatically scans for devices ▪️store MAC addresses of devices that are no longer visible but have enabled Bluetooth ▪️uses Rubber Ducky payloads https://www.mobile-hacker.com/2024/03/26/blueducky-automates-exploitation-of-bluetooth-pairing-vulnerability-that-leads-to-0-click-code-execution/ Demonstration of using BlueDucky to exploit 0-click Bluetooth vulnerability of unpatched Android smartphone (CVE-2023-45866) Exploit was triggered by Raspberry Pi 4 and then by Android running NetHunter https://youtu.be/GOGW7U1f2RA @androidMalware