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In The Media

Biggest Myth In the History of Human Programming

by Larry Chiang on March 1, 2026


Chapter 1 to Chapter 14’s an “Easter Egg” at #ch1 to #ch14. Including #ch2 which’s chapter 2 at my house in Napa California

http://www.youtube.com/watch?v=ejeIz4EhoJ0


On 09-09-39, “What They Will NEVER Teach You at Stanford Business School” debuts at 300 w 44th St at New York Fashion Week’s front row
http://www.youtube.com/watch?v=QXIaNZi3mHQ

What A Super Model Can Teach a Harvard MBA About Credit www.slideshare.net/larrychiang/what-a-super-model-can-teach-a-harvard-mba-about-credit

American Express hosts me mentoring you about FICO scores at New York Fashion Week
t.co/inxTmZAj

My video boils down 20,000 hours and moves you to the right on the entrepreneur bell curve 
http://www.youtube.com/watch?v=eudADPfTWiE


Steve Jobs Texted me on 650-283-8008 in the same way that Mr Jobs called Bill Hewlett https://x.com/superSaiyanSkai/status/1941392367304761636/video/1


Larry Chiang
Fund of Founders
Founding Stanford EIR
@duck9 alum, Deeply Understood Capital Credit Chinese Knowledge 9
Solo Founder Uber API
650-566-9600 Office
650-566-9696 Direct
Cell: 415-720-8500 

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Dario Amodei just dismantled the biggest myth in the AI industry.
Open source AI isn’t free. It never was.
Amodei: “It’s not free. You have to run it on inference and someone has to make it fast on inference.”
For decades, open source meant something real. It meant a teenager in a basement could download the same tools as a Fortune 500 company. Could read the code. Could modify it. Could build something that competed with the giants.
That was genuine democratization. That actually happened.
AI is different. Fundamentally. Physically. In ways the ideology hasn’t caught up to yet.
Downloading the weights is the easy part.
The part that actually costs something is turning the weights into a running system. Into responses. Into intelligence operating in real time at scale.
That requires compute. Power. Infrastructure. The kind measured in billions of dollars and years of construction.
Amodei: “These are big models. They’re hard to do inference on. Ultimately you have to host it on the cloud. The people who host it on the cloud do inference.”
The open source debate was never about who owns the model.
It was always about who owns the cloud.
And Amodei goes further. When a competitor drops a new open model, he doesn’t ask whether it’s open or closed. He doesn’t care about the licensing. He doesn’t engage the ideology.
Amodei: “I don’t think it mattered that DeepSeek is open source. I think I ask, is it a good model? Is it better than us at the things that matter? That’s the only thing that I care about.”
That’s the ruthless clarity of someone actually trying to win.
While the media debates licensing frameworks, Amodei is asking one question.
Is it better. Everything else is a distraction.
Amodei: “I don’t think open source works the same way in AI that it has worked in other areas. Here we can’t see inside the model.”
This isn’t Linux. You can’t read it. You can’t fork it. You can’t understand it the way generations of developers understood the tools they inherited.
You can download it. And then you need a data center to run it.
The teenager in the basement who was supposed to be empowered by this revolution needs a billion dollars of infrastructure before the empowerment starts.
The era of the basement coder rewriting civilization on a laptop is over.
The future belongs to whoever commands the compute, owns the power grid, and can actually turn the intelligence on.
Open weights without infrastructure isn’t democratization.
It’s a promise the physics of the universe won’t let us keep.

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