『Vīta Brevis, Wit Artefāctōrum Ætērna Podcast』のカバーアート

Vīta Brevis, Wit Artefāctōrum Ætērna Podcast

Vīta Brevis, Wit Artefāctōrum Ætērna Podcast

著者: Ash Stuart
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Exploring innovation, progress and achievement: a first-principles approach to everything that matters; combining history, epistemology, economics, anthropology, geopolitics, finance, philology, etymology and more... for, life is short, knowledge forever.

ashstuart.substack.comAsh Stuart
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  • TecC 24 - Reckoning Reality’s True Rules
    2025/07/11

    In the previous episode we discussed the emergence of philosophy and early science - in other words, the systematic inquiry into things around us. Today let’s look at what’s perhaps the empowering means of pursuing such inquiry. This likely more than many other topics we have covered straddles both ‘artefactual’ and ‘institutional’ in the current technocentric paradigm.

    It’s just after dinner and our...

    Visit my Substack for the full article.

    Article written by Ash Stuart

    Images and voice narration generated by AI

    Further Reading & Reference

    * Ash's other original referenced in this one: Conc 04: To Geek or Not to Geek: About Structure.

    * Al-Rashid, Moudhy. (2025). Between Two Rivers: Ancient Mesopotamia and the Birth of History. W. W. Norton & Company. ISBN 978-1324036425.

    * Devlin, Keith. (2012). Introduction to Mathematical Thinking. ISBN 978-0615653631.

    * Life by the Numbers. (1988). PBS Series.



    This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit ashstuart.substack.com
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    17 分
  • TecC 24 [Teas] - Reckoning Reality’s True Rules
    2025/07/09

    What drives the leap from noticing to knowing? When does practical pressure spark breakthrough thinking?

    Some innovations emerge not from luxury but from necessity. Not from theoretical curiosity but from urgent needs that demand solutions. But what happens when such pressing requirements collide with systematic minds?

    How do breakthroughs transform from local fixes into universal foundations? What makes certain innovations so successful they become invisible - quietly enabling everything that follows without announcing themselves?

    Why do some discoveries bridge seemingly unrelated domains? How do minds find connections where others see only separation? And what determines whether such connections become mere curiosities or transformative breakthroughs?

    There's a pattern in how breakthrough thinking unfolds. A progression from scattered insights to unified approaches. From ad hoc solutions to something far more powerful. But what triggers this progression? What separates innovations that remain niche from those that reshape everything?

    Consider the paradox: the most foundational breakthroughs often feel inevitable in retrospect, yet were far from obvious in the moment. They solve problems we didn't even realize we had. They create capabilities we didn't know we needed.

    How do such innovations persist across time and spread across cultures? What gives them staying power when so many other promising ideas fade away?

    These questions point toward something profound about how breakthrough thinking actually works. About the conditions that foster transformative innovation. About why some solutions become indispensable while others remain forgotten.

    Join Ash Stuart as he reveals the patterns behind one such breakthrough - an innovation so fundamental that its influence shapes how we approach everything.

    Audio generated by AI



    This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit ashstuart.substack.com
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    2 分
  • AISH 03 - The Case of the Talking Symbols: The Adventures of Ashlock Holmes
    2025/07/06

    Ever wondered how artificial intelligence really works beneath the hype? Behind every AI breakthrough lies a deceptively simple idea waiting to be understood. Follow Ashlock Holmes through conversations with Dr. Clodson as they ponder and decode the mysteries of machine intelligence, one dialogue at a time.

    In this adventure, Holmes announces he's discovered how to calculate exactly how closely related any two ideas are - claiming this breakthrough explains how those "you might also like" suggestions actually work.

    But if machines can figure out that two things are similar and predict what you want based on that similarity, what does that tell us about understanding itself? Are they truly grasping what you mean... or have they just become extraordinarily good guessers? The answer to who really knows what you need before you do might be right under your nose.

    Based on Conc 03 - It’s Meaning Cats and Dogs.

    Dialogue conceived and designed by Ash Stuart in collaboration with Claude (4 Sonnet).

    Image and voices generated by AI (OpenAI models)



    This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit ashstuart.substack.com
    続きを読む 一部表示
    19 分

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