AI Dynamics

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  • Yann LeCun’s Career Reflects How AI Innovation Really Happens

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    @pascal_bornet

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    ๐—ฌ๐—ฎ๐—ป๐—ป ๐—Ÿ๐—ฒ๐—–๐˜‚๐—ปโ€™๐˜€ ๐—ฐ๐—ฎ๐—ฟ๐—ฒ๐—ฒ๐—ฟ ๐—ฎ๐—น๐˜„๐—ฎ๐˜†๐˜€ ๐—บ๐—ฎ๐—ธ๐—ฒ๐˜€ ๐—บ๐—ฒ ๐˜๐—ต๐—ถ๐—ป๐—ธ ๐—ฎ๐—ฏ๐—ผ๐˜‚๐˜ ๐—ต๐—ผ๐˜„ ๐—ถ๐—ป๐—ป๐—ผ๐˜ƒ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฟ๐—ฒ๐—ฎ๐—น๐—น๐˜† ๐—ต๐—ฎ๐—ฝ๐—ฝ๐—ฒ๐—ป๐˜€. Today, deep learning powers much of modern AI. But when Yann LeCun began working on neural networks in the 1980s, many researchers

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  • Europe Backs $1B Bet Challenging LLM Roadmap with LeCun
    Europe Backs $1B Bet Challenging LLM Roadmap with LeCun

    By

    @pascal_bornet

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    ๐—˜๐˜‚๐—ฟ๐—ผ๐—ฝ๐—ฒ ๐—ท๐˜‚๐˜€๐˜ ๐—ฏ๐—ฎ๐—ฐ๐—ธ๐—ฒ๐—ฑ ๐—ฎ $๐Ÿญ๐—• ๐—ฏ๐—ฒ๐˜ ๐˜๐—ต๐—ฎ๐˜ ๐—ฐ๐—ต๐—ฎ๐—น๐—น๐—ฒ๐—ป๐—ด๐—ฒ๐˜€ ๐˜๐—ต๐—ฒ ๐—ฒ๐—ป๐˜๐—ถ๐—ฟ๐—ฒ ๐—Ÿ๐—Ÿ๐—  ๐—ฟ๐—ผ๐—ฎ๐—ฑ๐—บ๐—ฎ๐—ฝ. ๐—ฌ๐—ฎ๐—ป๐—ป ๐—Ÿ๐—ฒ๐—–๐˜‚๐—ป has spent years arguing that much of todayโ€™s AI is essentially โ€œglorified autocomplete.โ€ Now he has $1 billion to prove there may be

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  • Reality of Agentic AI: Beyond Labels and Simple Workflows
    Reality of Agentic AI: Beyond Labels and Simple Workflows

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    @pascal_bornet

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    ๐—ง๐—ต๐—ฒ ๐—ฟ๐—ฒ๐—ฎ๐—น๐—ถ๐˜๐˜† ๐—ผ๐—ณ ๐—”๐—ด๐—ฒ๐—ป๐˜๐—ถ๐—ฐ ๐—”๐—œ ๐—ฟ๐—ถ๐—ด๐—ต๐˜ ๐—ป๐—ผ๐˜„. โ†’ Many people are talking about AI agents. Only a few are actually building systems that generate real value. โ†’ Most โ€œAI agentsโ€ today are still assistants or simple workflows with a new label. That gap is

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  • Anthropic analyzes which jobs AI could replace
    Anthropic analyzes which jobs AI could replace

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    @pascal_bornet

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    BREAKING: ๐€๐ง๐ญ๐ก๐ซ๐จ๐ฉ๐ข๐œ just released one of the most detailed analyses yet of which jobs ๐š๐ซ๐ญ๐ข๐Ÿ๐ข๐œ๐ข๐š๐ฅ ๐ข๐ง๐ญ๐ž๐ฅ๐ฅ๐ข๐ ๐ž๐ง๐œ๐ž could potentially replace. The headlines escalated quickly. Some economists are already warning about a possible ๐†๐ซ๐ž๐š๐ญ

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  • Veteran Engineer Solves Critical Engine Failure Through Experience
    Veteran Engineer Solves Critical Engine Failure Through Experience

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    @pascal_bornet

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    An enormous ship engine suddenly stopped working. Teams of engineers tried to fix it. Hours passed. Then days. Nothing worked. Finally, the owners called a veteran engineer with decades of experience. He walked around the engine slowly, studying it in silence. After a few

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  • Open Source Developers Power Modern Tech Stack Reality
    Open Source Developers Power Modern Tech Stack Reality

    By

    @pascal_bornet

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    This diagram might be the most honest picture of the modern tech stack. Look closely. โ†ณ Unpaid open-source developers holding everything together
    โ†ณ AWS + Cloudflare doing most of the heavy lifting
    โ†ณ AI layered on top
    โ†ณ Microsoftโ€ฆ vibing aggressively somewhere in the middle

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  • Automation Amplifies: Three Software Development Approaches Today
    Automation Amplifies: Three Software Development Approaches Today

    By

    @pascal_bornet

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    I keep seeing three ways teams build software today. Steady progress โ‰ˆ Careful architecture. Testing. Discipline. Reckless speed โ‰ˆ Ship fast. Fix later. Vibe coding โ‰ˆ Ask AI. Copy. Deploy. But automation has a rule:
    It amplifies whatever system it touches. Good

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  • Historical Tech Innovations: Electric Scooters and Rotating Wheel Cars

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    @pascal_bornet

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    ๐—œ๐—ป๐˜ƒ๐—ฒ๐—ป๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ณ๐—ฟ๐—ผ๐—บ ๐Ÿญ๐Ÿต๐Ÿฎ๐Ÿฌ ๐˜๐—ผ ๐Ÿญ๐Ÿต๐Ÿฒ๐Ÿฌ. Sometimes I forget how many โ€œmodernโ€ ideas already existed decades ago. Electric scooters were already there.
    Even cars with ๐Ÿต๐Ÿฌ-๐—ฑ๐—ฒ๐—ด๐—ฟ๐—ฒ๐—ฒ ๐—ฟ๐—ผ๐˜๐—ฎ๐˜๐—ถ๐—ป๐—ด ๐˜„๐—ต๐—ฒ๐—ฒ๐—น๐˜€. It reminds me that innovation is often not about

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  • Simplifying Complexity: The Key to AI Breakthroughs

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    @pascal_bornet

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    Sometimes the hardest part of intelligence is not solving complexity. Itโ€™s explaining it simply. Take f(x) = sin(x). On paper, itโ€™s abstract. Visualized like this, it suddenly becomes obvious. In AI, I see the same pattern. The biggest breakthroughs often come from people who

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  • Automation 101: Eliminate, Optimize, Standardize Then Automate
    Automation 101: Eliminate, Optimize, Standardize Then Automate

    By

    @pascal_bornet

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    Automation 101. Over the years, I have seen many automation projects fail for the same reason: teams try to automate the process before fixing it. The order should be simple: Eliminate what should not exist Optimize what remains Standardize how it is done Then

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