#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
🌎 Off the coast of Australia, the mysterious "pink lakes" like Lake Hillier owe their color to the algae Dunaliella salina, which produce red pigments in salty environments. Lake Hillier’s pink hue remains stable even when bottled, due to the unique chemistry of its saline water. ✨
#ocean⚡#mystery⚡#algae
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🌎 Red tides sometimes turn the ocean a rusty red or brown—caused by massive blooms of algae packed with pigments. These blooms can release toxins that harm fish and even impact local air quality, making ocean color changes a sign of dramatic ecological shifts. ✨
#ocean⚡#algae⚡#pigments
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🌎 Red rain fell in the Indian state of Kerala in 2001, coloring streets and clothing. Scientists found the cause was airborne spores from local algae cells. Some showers were bright red for up to two months. ✨
#phenomena⚡#weather⚡#algae
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