#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
🌎 On the island of Märket in the Baltic Sea, the Finland-Sweden border cuts through a tiny lighthouse. The border was shifted in 1985 so both nations could share the landmark, creating a zigzag international line only 500 meters long. ✨
#borders⚡#geography⚡#lighthouse
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🌎 The Flannan Isles Lighthouse mystery remains unsolved: in December 1900, three lighthouse keepers disappeared from a remote Scottish island. No bodies or clues to their fate were found, and weather records suggest a sudden storm struck the area. The lighthouse was left locked, with meals untouched and logs stopping abruptly on December 15. ✨
#mystery⚡#lighthouse⚡#Scotland
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