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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 #65399 · 04/13/2026, 05:13 AM

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🚀 AI TRENDS | Bitcoin Mining Centralization and Edge AI Market Growth Projected Bitcoin mining is anticipated to become increasingly centralized, according to Alex Thorn, head of Galaxy Research. According to NS3.AI, Thorn's insights suggest a shift in the mining landscape, potentially impacting the decentralization that has been a hallmark of the cryptocurrency. Meanwhile, the edge AI market is expected to experience significant growth. Grand View Research forecasts that the market will expand from approximately $25 billion in 2025 to $119 billion by 2033, indicating a trend towards more localized AI applications. #BitcoinMining#Centralization#EdgeAI#MarketGrowth#Decentralization#AITrends#GalaxyResearch#NS3AI#GrandViewResearch#LocalizedAI#BTC

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