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Source channel @githubtrending · Post #14826 · Jun 12

#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data. https://github.com/FareedKhan-dev/all-rag-techniques

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Libreware

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

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⁭#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

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