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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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AI & Law

@ai_and_law · Post #99 · 08/30/2023, 07:04 AM

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Zoom Addresses EU Privacy Concerns and Updates Terms of Service Greetings! In response to discussions about potential EU privacy law implications, Zoom issues a statement and revises its Terms of Service. The focus? Ensuring customer data isn't utilized to train AI models. Zoom's statement and Terms affirm that user-generated content, including audio, video, chat, and more, isn't employed for training Zoom's or any third-party AI models. This step aims to dispel any concerns. Zoom initially shared its statement on August 7 and later updated it on August 11, aligned with the revised Terms. The shared stance now unequivocally states, "Zoom does not use any of your customer content to train AI models." Earlier, a Stack Diary article flagged changes to Zoom's March Terms, raising potential concerns about broad data utilization for AI model training. Zoom's quick response aims to address these concerns and reaffirm privacy commitments. #Zoom#PrivacyMatters#TermsOfService#AIModels#DataProtection#PrivacyLaw#TechUpdates

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