Machine Learning Street Talk (MLST)

The 3 Laws of Knowledge [César Hidalgo]


Listen Later

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


---

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?


---

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


...more
View all episodesView all episodes
Download on the App Store

Machine Learning Street Talk (MLST)By Machine Learning Street Talk (MLST)

  • 4.7
  • 4.7
  • 4.7
  • 4.7
  • 4.7

4.7

90 ratings


More shows like Machine Learning Street Talk (MLST)

View all
Data Skeptic by Kyle Polich

Data Skeptic

479 Listeners

The a16z Show by Andreessen Horowitz

The a16z Show

1,095 Listeners

Super Data Science: ML & AI Podcast with Jon Krohn by Jon Krohn

Super Data Science: ML & AI Podcast with Jon Krohn

302 Listeners

NVIDIA AI Podcast by NVIDIA

NVIDIA AI Podcast

333 Listeners

Y Combinator Startup Podcast by Y Combinator

Y Combinator Startup Podcast

228 Listeners

Practical AI by Practical AI LLC

Practical AI

204 Listeners

ManifoldOne by Steve Hsu

ManifoldOne

95 Listeners

Google DeepMind: The Podcast by Hannah Fry

Google DeepMind: The Podcast

207 Listeners

Dwarkesh Podcast by Dwarkesh Patel

Dwarkesh Podcast

517 Listeners

Big Technology Podcast by Alex Kantrowitz

Big Technology Podcast

501 Listeners

No Priors: Artificial Intelligence | Technology | Startups by Conviction

No Priors: Artificial Intelligence | Technology | Startups

130 Listeners

This Day in AI Podcast by Michael Sharkey, Chris Sharkey

This Day in AI Podcast

228 Listeners

AI + a16z by a16z

AI + a16z

36 Listeners

Training Data by Sequoia Capital

Training Data

40 Listeners

Complex Systems with Patrick McKenzie (patio11) by Patrick McKenzie

Complex Systems with Patrick McKenzie (patio11)

134 Listeners