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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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@abmedia_news · Post #24028 · 04/21/2026, 06:32 AM
【🚀 交易市場｜日本啟動 Canton 網路驗證專案、測試國債作為數位抵押品 】 #Japan#Canton#JPX 📍 請見報導： https://abmedia.io/japan-launch-trial-for-digital-collateral-management-using-japanese-government-bonds 📍 訂閱鏈新聞頻道：https://linktr.ee/abmedia.io
@venturevillagewall · Post #3943 · 01/21/2025, 07:00 PM
Circle Expands USDC Ecosystem 🚀 Circle announces key developments: - Acquired RWA platform Hashnote. - Partnered with DRW to promote USDC and Ondo Dollar (USDY). - USDC and USYC launching on Canton blockchain. 💵 50M USDC minted (approx. $50.03M). Bitcoin ETFs now hold over 1.1M BTC (~5.7% supply). Details here | More on Bitcoin ETFs | Canton news #USDC#Circle#Blockchain#Crypto#Finance#USYC#Bitcoin#ETFs#Investments#Hashnote#DRW#DigitalAssets#Canton#Markets#CryptoTrends#Tokenization#WhaleAlert#Funding#Sustainability#DeFi#Innovation