Do Large Language Models Increase Collective Knowledge?

César Hidalgo has spent years trying to answer a deceptively simple question: What is knowledge, and why is it so hard to move around?

We all have this intuition that knowledge is just... information. Write it down in a book, upload it to GitHub, train an AI on it—done. But César argues that's completely wrong. Knowledge isn't a thing you can copy and paste. It's more like a living organism that needs the right environment, the right people, and constant exercise to survive.

Guest: César Hidalgo, Director of the Center for Collective Learning

1. Knowledge Follows Laws (Like Physics)

2. You Can't Download Expertise

3. Why Big Companies Fail to Adapt

4. The "Infinite Alphabet" of Economies

If you think AI can just "copy" human knowledge, or that development is just about throwing money at poor countries, or that writing things down preserves them forever—this conversation will change your mind. Knowledge is fragile, specific, and collective. It decays fast if you don't use it.

The Infinite Alphabet [César A. Hidalgo]

https://www.penguin.co.uk/books/458054/the-infinite-alphabet-by-hidalgo-cesar-a/9780241655672

https://x.com/cesifoti

Rescript link.

https://app.rescript.info/public/share/eaBHbEo9xamwbwpxzcVVm4NQjMh7lsOQKeWwNxmw0JQ

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TIMESTAMPS:

00:00:00 The Three Laws of Knowledge

00:02:28 Rival vs. Non-Rival: The Economics of Ideas

00:05:43 Why You Can't Just 'Download' Knowledge

00:08:11 The Detective Novel Analogy

00:11:54 Collective Learning & Organizational Networks

00:16:27 Architectural Innovation: Amazon vs. Barnes & Noble

00:19:15 The First Law: Learning Curves

00:23:05 The Samuel Slater Story: Treason & Memory

00:28:31 Physics of Knowledge: Joule's Cannon

00:32:33 Extensive vs. Intensive Properties

00:35:45 Knowledge Decay: Ise Temple & Polaroid

00:41:20 Absorptive Capacity: Sony & Donetsk

00:47:08 Disruptive Innovation & S-Curves

00:51:23 Team Size & The Cost of Innovation

00:57:13 Geography of Knowledge: Vespa's Origin

01:04:34 Migration, Diversity & 'Planet China'

01:12:02 Institutions vs. Knowledge: The China Story

01:21:27 Economic Complexity & The Infinite Alphabet

01:32:27 Do LLMs Have Knowledge?

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REFERENCES:

Book:

[00:47:45] The Innovator's Dilemma (Christensen)

https://www.amazon.com/Innovators-Dilemma-Revolutionary-Change-Business/dp/0062060244

[00:55:15] Why Greatness Cannot Be Planned

https://amazon.com/dp/3319155237

[01:35:00] Why Information Grows

https://amazon.com/dp/0465048994

Paper:

[00:03:15] Endogenous Technological Change (Romer, 1990)

https://web.stanford.edu/~klenow/Romer_1990.pdf

[00:03:30] A Model of Growth Through Creative Destruction (Aghion & Howitt, 1992)

https://dash.harvard.edu/server/api/core/bitstreams/7312037d-2b2d-6bd4-e053-0100007fdf3b/content

[00:14:55] Organizational Learning: From Experience to Knowledge (Argote & Miron-Spektor, 2011)

https://www.researchgate.net/publication/228754233_Organizational_Learning_From_Experience_to_Knowledge

[00:17:05] Architectural Innovation (Henderson & Clark, 1990)

https://www.researchgate.net/publication/200465578_Architectural_Innovation_The_Reconfiguration_of_Existing_Product_Technologies_and_the_Failure_of_Established_Firms

[00:19:45] The Learning Curve Equation (Thurstone, 1916)

https://dn790007.ca.archive.org/0/items/learningcurveequ00thurrich/learningcurveequ00thurrich.pdf

[00:21:30] Factors Affecting the Cost of Airplanes (Wright, 1936)

https://pdodds.w3.uvm.edu/research/papers/others/1936/wright1936a.pdf

[00:52:45] Are Ideas Getting Harder to Find? (Bloom et al.)

https://web.stanford.edu/~chadj/IdeaPF.pdf

[01:33:00] LLMs/ Emergence

https://arxiv.org/abs/2506.11135

Person:

[00:25:30] Samuel Slater

https://en.wikipedia.org/wiki/Samuel_Slater

[00:42:05] Masaru Ibuka (Sony)

https://www.sony.com/en/SonyInfo/CorporateInfo/History/SonyHistory/1-02.html