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Source channel @githubtrending · Post #14826 · Jun 12

#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

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@emagzinewspars · Post #9460 · 11/03/2025, 03:27 AM

#The_Bloomberg🇺🇸📕[PDF]⬇️ #November2025 #Monthly_Magazines For learning, for free(dom). @backupofmagazines This issue pits #GavinNewsom against a shifting #USPolitics map while probing the supposed #AIBubble, from frothy valuations to real-world productivity. A climate-forensics read asks whether #CloudSeeding worsened Dubai’s deadly storm—at the nexus of #ExtremeWeather and #ClimateChange. The geo-economics file tracks India’s wobbling investments, China’s expanding #Ports, and weaponized #SupplyChains. For investors, the issue weighs #ETFs, #401k tweaks, #BigTech concentration risk, and hedges in #Europe and #Gold. Lifestyle detours sample Utah powder and the dive-bar revival. It’s a brisk tour of power, money, and culture in a volatile world. #Markets#Investing#Energy#MiddleEast#Africa#Healthcare#Birkenstocks