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Source channel @githubtrending · Post #14826 · Jun 12

#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data. https://github.com/FareedKhan-dev/all-rag-techniques

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The Digi Doodles

@Digi_doodles · Post #622 · 08/01/2025, 10:02 AM

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WeTransfer’s AI Terms: Are Artists Losing Control?🃏 July 28, 2025 · The Art Newspaper A quiet shift with loud consequences. 👂 WeTransfer has updated its terms of service to allow the use of uploaded files for AI training — sparking concern among digital artists and creatives. While the platform claims “anonymized and aggregated” data use, critics warn this could jeopardize intellectual property. What’s at stake: — Artists may unknowingly feed generative AI tools — Lack of opt-out or clear consent for creative works — Questions around ownership, credit & ethics Another wake-up call in the ongoing conversation around AI, authorship, and data rights📖 #AIArt#DigitalRights#WeTransfer#ArtAndTech#DataEthics

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