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Source channel @githubtrending · Post #15239 · Oct 21

#python#artificial_intelligence#cloud_ml#computer_systems#courseware#deep_learning#edge_machine_learning#embedded_ml#machine_learning#machine_learning_systems#mobile_ml#textbook#tinyml You can learn how to build real-world AI systems from start to finish with an open-source textbook originally from Harvard University. It teaches you not just how to train AI models but how to design scalable systems, manage data pipelines, deploy models in production, monitor them continuously, and optimize for devices like phones or IoT gadgets. This helps you become an engineer who can create efficient, reliable, and sustainable AI systems that work well in practice. The book offers hands-on labs, community support, and free online access, making it easier to gain practical skills in machine learning systems engineering. https://github.com/harvard-edge/cs249r_book

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Venture Village Wall 🦄

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

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