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Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability.
https://github.com/langchain-ai/rag-from-scratch
🌍 In Chile's Atacama Desert, rare fog called "camanchaca" drifts inland from the Pacific. Some plants here survive by absorbing water directly from this fog, not from rainfall. ✨
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🌍 Some arid desert landscapes feature ancient, dried-up riverbeds called wadis that can flood suddenly after rare rains, quickly turning from bare channels to rushing streams in a matter of hours. ✨
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🌍 Libya’s Libyan Desert holds sand seas with dunes reaching up to 180 meters tall. These giant dunes constantly shift with the wind, creating landscapes that can look completely different in just a few years. ✨
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🌍 In the Taklamakan Desert of China, some sand dunes reach up to 300 meters tall. Shifting winds keep these giant dunes moving, constantly reshaping the landscape year after year. ✨
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🌍 The Atacama Desert in Chile is so dry that some weather stations have never recorded rain. Its Mars-like soils are studied by scientists searching for signs of life in extreme environments. ✨
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🌍 The Namib Desert is thought to be the oldest desert on Earth, with arid conditions lasting for at least 55 million years—far longer than any other known desert. ✨
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