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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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AI & Law

@ai_and_law · Post #124 · 09/27/2023, 07:04 AM

UK: CMA Releases Principles for Responsible AI Development Hello, everyone! The Competition and Markets Authority (CMA) has unveiled a set of principles to ensure the responsible development and use of foundation models (FMs) in AI. Foundation models, like ChatGPT and Office 365 Copilot, are versatile AI systems poised to revolutionize various sectors. The CMA's report lays out these guiding principles, with a focus on safeguarding consumer protection and fostering healthy competition in the AI industry. As AI rapidly integrates into our daily lives, the CMA recognizes the need for proactive intervention. These principles aim to strike a balance between promoting AI's potential for innovation and ensuring consumer safety. The CMA's proposed guiding principles focus on crucial areas like accountability, access, diversity, choice, flexibility, fairness, and transparency. These principles aim to guide FM developers and deployers toward responsible AI development and use. The CMA plans to engage extensively with stakeholders to refine these principles further. Stay tuned for updates in early 2024 as they continue shaping AI markets for the betterment of all. #ResponsibleAI#AIRegulation#ConsumerProtection#Competition#FoundationModels#CMAAIprinciples