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Data Science at Home

Data Science at Home

著者: Francesco Gadaleta
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Technology, AI, machine learning and algorithms. Come join the discussion on Discord! https://discord.gg/4UNKGf3Copyright 2024 datascienceathome.com All rights reserved. 政治・政府
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  • Your Favorite AI Startup is Probably Bullshit (Ep. 287)
    2025/07/26

    The brutal truth about why Silicon Valley is blowing billions on glorified autocomplete while pretending it's the next iPhone.

    We're diving deep into the AI investment circus where VCs who can't code are funding companies that barely understand their own technology. From blockchain déjà vu to the "ChatGPT wrapper" economy—this episode will make you question every AI valuation you've ever seen.

    Fair warning: We're naming names and calling out the hype. Don't listen if you work at a "revolutionary AI startup" that's just OpenAI's API with a pretty interface.

    #AIBubble #VentureCapital #TechReality #StartupBullshit

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    12 分
  • Tech's Dumbest Mistake: Why Firing Programmers for AI Will Destroy Everything (Ep. 286) [RB]
    2025/07/07

    From the viral article "Tech's Dumbest Mistake: Why Firing Programmers for AI Will Destroy Everything" on my newsletter at https://defragzone.substack.com/p/techs-dumbest-mistake-why-firing

    here are my thoughts about AI replacing programmers...

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    NEW TO DATA SCIENCE AT HOME?

    Welcome! Data Science at Home explores the latest in AI, data science, and machine learning. Whether you’re a data professional, tech enthusiast, or just curious about the field, our podcast delivers insights, interviews, and discussions. Learn more at https://datascienceathome.com

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    Don’t forget to like, subscribe, and hit the 🔔 for updates on the latest in AI and data science!

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    19 分
  • Brains in the Machine: The Rise of Neuromorphic Computing (Ep. 285)
    2025/06/18

    In this episode of Data Science at Home, we explore the fascinating world of neuromorphic computing — a brain-inspired approach to computation that could reshape the future of AI and robotics. The episode breaks down how neuromorphic systems differ from conventional AI architectures like transformers and LLMs, diving into spiking neural networks (SNNs), their benefits in energy efficiency and real-time processing, and their limitations in training and scalability. Real-world applications are highlighted, including low-power drones, hearing aids, and event-based cameras. Francesco closes with a vision of hybrid systems where neuromorphic chips and LLMs coexist, blending biological inspiration with modern AI.

    📚 References

    • SpikingJelly: https://github.com/fangwei123456/spikingjelly

    • Norse: https://github.com/norse/norse

    • IBM TrueNorth: https://www.millionairematch.com

    • AGNTCY — The open source collective building the Internet of Agents 🌐 https://www.agntcy.org

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    24 分

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