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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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@googlefactss · Post #40364 · 12/19/2025, 07:02 PM

Chemists at UC Berkeley created a new catalytic process that turns plastic bags and bottles (polyolefins) into gases like propylene and isobutylene. These gases are used to make new plastics like polypropylene. The process uses cheap solid catalysts and can be scaled up for industrial use. This method helps recycle plastics better and supports a circular economy by turning waste into new materials. 🔄♻️ [Source] @googlefactss #plasticrecycling#catalysis#polyolefins#circularEconomy#sustainability#chemistry#innovation

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@emagzinewspars · Post #9464 · 11/03/2025, 03:27 AM

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