#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
➡️New build available for Xiaomi POCO M3/Redmi 9T (chime)
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➡️New build available for Xiaomi POCO M3/Redmi 9T (chime)
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🪐 One of the largest samples of fast radio bursts (FRBs) ever recorded comes from the Canadian Hydrogen Intensity Mapping Experiment (CHIME), which has detected thousands of these brief, mysterious flashes from all directions across the sky. Each FRB is a burst of radio energy that lasts just milliseconds, often releasing more power than our Sun emits in days, and their unpredictable appearances continue to challenge scientists searching for their true origins. ✨
#FRB⚡#CHIME⚡#astronomy⚡#nasa⚡#galaxy⚡#stars⚡#universe⚡#cosmos⚡#space
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