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What We're Building: An Open-Weight Canadian Model Series
The model is the smallest part of the story. Here's what it is, what it isn't, and what comes next. Today we shipped flash-1-mini. It's a 4-billion-parameter open-weight model, fine-tuned for Canadian context, bilingual in English and French, that runs on a laptop with no cloud dependency. You can download it, run it offline, and own it. The weights are yours. I want to write about what it is, what it isn't, and what comes after — because the model itself is the smallest part of the story.
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.
I Almost Told a Lawyer to Build His Own AI
A lawyer friend — call him Mark — called me this week. He and another friend had spent the weekend trying to run an 8 billion parameter language model on a 16 gigabyte laptop. Mark thought he was going to show his friend something impressive. The output was gibberish. Incoherent strings of text that no junior associate would have signed off on. He'd come to me because he wanted to know what hardware to buy next. On the call, I didn't know. What I did know was NVIDIA's software stack. I'd
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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
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Your ChatGPT and Claude Conversations Are Court Evidence
Greg Brockman's journal became Exhibit 161 this week. The next chapter writes itself. Someone's ChatGPT history becomes Exhibit 162. That sentence sounds like speculation. It isn't. The infrastructure is already in place. The court orders are already in place. The only thing missing is a famous enough defendant for the headline to break the way Brockman's did. The court order most people haven't read In May 2025, Magistr
Read essayFrom the series · 90-Day Action Plan to Surviving AI
The Grief
After I decided to kill SimpleDirect, I didn't tell anyone for two weeks.
More on Own Your Tech
Three essays from the archive on a different angle.
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 essayOne Rack Is a Cloud
What colocation is, and why most AI founders have never heard of it
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I Almost Told a Lawyer to Build His Own AI
A lawyer friend — call him Mark — called me this week. He and another friend had spent the weekend trying to run an 8 billion parameter language model on a 16 gigabyte laptop. Mark thought he was going to show his friend something impressive. The output was gibberish. Incoherent strings of text that no junior associate would have signed off on. He'd come to me because he wanted to know what hardware to buy next. On the call, I didn't know. What I did know was NVIDIA's software stack. I'd
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Three things from across the site you may not have found yet.
You might not have read this
A couple of older essays we think are worth a second look.
Why I'm fine-tuning a small model (and why it runs on your laptop)
I'm training an AI model. It's going to run on a laptop. Three weeks ago I would have told you I was training a 70-billion-parameter model, the kind of thing that needs a data center to breathe. I'm not. I'm training a 4-billion-parameter model that runs on a Mac Mini. If the smaller one works, a larger companion model may follow. But the 4B is the bet. This is the first post in a series where I'll share what I'm building, why,
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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.
Read this essayRun the numbers yourself
Free calculators and assessments. No email wall.
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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