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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook 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

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Crypto M - Crypto News

@CryptoM · Post #64697 · 04/09/2026, 02:44 PM

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🚀 Telegram's TON Blockchain Achieves Significant Speed Upgrade Telegram founder Pavel Durov announced a major upgrade to the TON blockchain, significantly enhancing its processing speed. According to Foresight News, the upgrade has increased block generation rates by six times and achieved sub-second transaction confirmations. Durov stated that this is the first of seven steps in his 'Make TON Great Again' (MTONGA) plan. The next step aims to reduce the already relatively low transaction fees by approximately six times to further improve network performance and cost competitiveness. #Telegram#TONBlockchain#PavelDurov#SpeedUpgrade#Blockchain#TransactionSpeed#MTONGA#ForesightNews#SubSecondConfirmations#TransactionFees#NetworkPerformance

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