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Fine-tuning your own AI doesn't cost $35,000. It cost us about $50.
Two A100 graphics cards. Spinning quietly in a Google datacenter. Five hours of training. About $50 in compute. That's what it cost us to fine-tune our own 4-billion-parameter AI model this week. The base model went from 30% accuracy on the tasks we care about to 98%. Read any article on fine-tuning costs and you'll see numbers between $5,000 and $35,000. One blog called it a 'CFO conversation.' Another listed 'hidden expenses' that could double your initial estimate. A third quoted team
Read storyFounder Reality is written by George Pu — $10M+ portfolio built by 27, no investors, no co-founders.
Latest Essays
What I'm thinking about right now.
Three Kinds of Cloud (and Why Two of Them Keep Getting Confused)
I sat down with a Canadian university last week. They were trying to articulate to industry partners what their compute offering would be. They knew "sovereign" was the right word. They couldn't define it for a buyer. They couldn't tell me what a partner would actually use it for that they couldn't already do on AWS in Montreal. That's not the university's failure. The industry calls three different things "cloud" and lets two
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GPU Cloud Shopping in Canada: Three Weeks Later
Three weeks ago I wrote a post called GPU Cloud Shopping in Canada: What's Actually Available. The short version: I checked every major cloud provider with a Canadian data center, trying to rent a current-generation GPU to train AI models in this country. Google Cloud Montreal had chips from 2017. AWS listed the right hardware but wouldn't let me actually run it. OVHcloud's H100s turned out to be in France, not Quebec. DigitalOc
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What fine-tuning actually costs (it's not what you think)
Training an AI model is assumed to cost millions of dollars. It's the single most common misconception in the space, and it's wrong by roughly two orders of magnitude for the activity most people actually want to do. This post is a short, concrete breakdown of what fine-tuning actually costs in 2026, what it doesn't cost, and where the real spend lives. I'm writing it now because 'how much does this cost' is the first question
Read essayFrom the series · The AI Displacement Series
The Path Forward
This is Chapter 7 of 7 in the AI Displacement Series.
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Three essays from the archive on a different angle.
The Lie Every $997 Trading Course Sells You
What two years of quant trading taught me before I shut it down.
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Why I Sold My Index Funds in February
Why the index gospel was built for a world that no longer exists.
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Why I'm Open-Sourcing My Portfolio
What active thesis investing actually looks like — and why I'll publish every bet I make.
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A couple of older essays we think are worth a second look.
Announcing Ghost Narrator: Self-Hosted AI Narration Stack
We publish about 200 blog posts a month on Founder Reality. Every post gets a narrated audio version — you can listen instead of read. The obvious solution was ElevenLabs. Best-in-class voice cloning, simple API, great output. $330/month for the scale we needed. We almost signed up. Then we tried something else. We ran an open-source model on a laptop. Qwen 3.5 14B for script rewriting, Qwen TTS for voice cloning. The whole pi
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What You Kill > What You Build
OpenAI killed Sora Not sunsetted. Killed. The product they hyped as the next ChatGPT. The one Disney was about to invest a billion dollars around. The one that was supposed to turn OpenAI into the creative engine of the AI era. Gone in an afternoon. The reason is almost boring in how obvious it is. Sora was eating compute - the most expensive resource on earth right now - while Anthropic was running away with the market tha
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Recent threads
The latest from @TheGeorgePu.
Canada's AI hardware reality check — what's actually available vs. what founders think they can buy.
GPU shipping is the tell. If you can't physically own the compute, you don't own your AI stack.
I only write code when it's 10/10 important. Slowing down is the real productivity move in 2026.
Mac Studio supply is crunched. Apple's quietly rationing M3 Ultra — AI builders feel it first.
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