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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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@CryptoM · Post #65359 · 04/13/2026, 02:14 AM

🚀 Japanese Firms Collaborate on Domestic AI Model Development SoftBank, NEC, Honda, and Sony Group have established a new company named 'Japan AI Foundation Model Development' to create domestic AI foundational models for Japanese businesses. According to Odaily, a SoftBank executive will lead the company, with Nippon Steel, Kobe Steel, Mitsubishi UFJ Bank, Sumitomo Mitsui Bank, and Mizuho Bank contributing financially. SoftBank and NEC will handle development, while Honda plans to apply the results to autonomous driving, with Preferred Networks also participating. The company intends to apply for a public call from the New Energy and Industrial Technology Development Organization, which, if selected, could provide support amounting to 1 trillion yen over five years starting in 2026. #JapaneseFirms#AI#SoftBank#NEC#Honda#SonyGroup#AIModelDevelopment#JapanAI#AutonomousDriving#NipponSteel#KobeSteel#MitsubishiUFJBank#SumitomoMitsuiBank#MizuhoBank#PreferredNetworks#PublicCall#NewEnergyIndustrialTechnology#TrillionYenSupport