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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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@githubtrending · Post #15234 · 10/18/2025, 11:30 AM

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#other#cti#cyberhunter#darkweb#deepweb#threat_intelligence deepdarkCTI is a free project that collects and shares cyber threat intelligence (CTI) from the deep and dark web, helping you stay aware of hidden cyber threats like stolen data, ransomware, and hacker activities. It gathers information from places like Telegram, Discord, hacker forums, and ransomware sites to provide useful indicators and patterns of cyber attacks. You can join their Telegram group to discuss and suggest new sources or support the project with donations. Using deepdarkCTI helps you detect threats early, improve your cybersecurity decisions, and protect your organization from cyber attacks more effectively. https://github.com/fastfire/deepdarkCTI

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