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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 #64458 · 04/09/2026, 01:01 AM

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🚀 Michael Saylor Suggests Bitcoin May Have Bottomed, Downplays Quantum Computing Risks PANews posted on X (formerly Twitter). Michael Saylor, founder and executive chairman of MicroStrategy, expressed at a Mizuho event that Bitcoin likely reached its bottom near $60,000 in early February. He attributed this bottoming more to a depletion of sellers rather than valuation factors. Saylor noted that current selling pressure is limited, with ETF inflows absorbing daily supply and corporations allocating treasury assets to Bitcoin, which sustains demand. Regarding the recent discussions on the threat of quantum computing, Saylor believes the risks are overstated. He stated that the threat remains theoretical and may not need to be addressed for several decades, by which time solutions will likely be available. #MichaelSaylor#Bitcoin#Bottomed#QuantumComputing#ETFInflows#Cryptocurrency#MicroStrategy#Blockchain#TreasuryAssets#CryptoDemand#BTC

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