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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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Venture Village Wall 🦄

@venturevillagewall · Post #3719 · 12/26/2024, 10:00 AM

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Nvidia's Earnings Shift Expected in 5 Years AI companies are struggling to earn enough to cover investments, according to David Kahn from Sequoia, who noted they should earn 6 times more. Currently, Nvidia leads AI earnings. SK Capital projects a shift in 3-5 years where solution developers like OpenAI will earn significantly more. This mirrors trends from the tech boom when software developers eventually outpaced hardware manufacturers. For detailed insights, read the full report here. #Nvidia#AI#Crypto#Sequoia#SKCapital#OpenAI#TechBoom#Earnings#Investments#MarketTrends#Software#Hardware#Developers#Graphics#Chips#GenerativeAI#InvestmentForecast#TechIndustry#BusinessModel#ValueChain#AIRevenue