#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
🌍 The world’s biggest human migration still happens every year in China, as hundreds of millions travel during Lunar New Year— the largest annual movement of people on Earth. ✨
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🌍 In 2022, the number of international migrants reached an estimated 281 million—more than triple the figure from 1970—making up 3.6% of the world’s total population today. ✨
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🌍 Since the 1990s, the number of people living outside their birthplace has more than doubled, with most international migration now happening between countries in Asia and Europe. ✨
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🌍 Tokyo’s Shibuya Crossing is one of the busiest pedestrian intersections in the world, where as many as 3,000 people can cross with every green light, illustrating dense urban flow. ✨
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