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While You Were Watching the Chatbots
Over the past two years, Canada quietly rebuilt the question of who controls its artificial intelligence. Not in one announcement. That's the point. There was never a single moment loud enough to make you look up. The decisions arrived in fragments — a Christmas Eve letter, a contribution agreement with a file number, a press release at a university most people don't follow, an MOU with the important parts blacked out. Each fragment was, on its own, small enough to ignore. Together they red
Read storyFounder Reality is written by George Pu — $10M+ portfolio built by 27, no investors, no co-founders.
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What I'm thinking about right now.
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
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The Journal That Exposed the President
Greg Brockman keeps a diary. Not a metaphor. A literal, decades-long, type-into-his-laptop journal that he started in college when he was deciding what to study. He kept it through Stripe. He kept it through founding OpenAI with Musk and Altman. He kept it through the brawl for control of the company in 2017 - the fight that's now being relitigated in a San Francisco courtroom. This week, his journal became Exhibit 161. Hun
Read essayFrom the series · 90-Day Action Plan to Surviving AI
The Commitment
After I started running experiments and having conversations, opportunities started appearing.
More on Own Your Tech
Three essays from the archive on a different angle.
Hardware Sovereignty Is the New Data Sovereignty
After I wrote about trying to buy a Mac Studio and failing, the replies kept circling the same question. "If I can't buy the hardware and I don't trust the cloud, what am I supposed to do?" That question led me somewhere I didn't expect. I Checked What GPUs You Can Actually Get in Canada Not the marketing pages. Not the pricing calculators either. The actual hardware you can spin up today in a Canadian data center. I went t
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We Swapped Our TTS Model. The Older, Free One Won.
When we launched Ghost Narrator, we used Fish Speech for voice cloning. It worked. The voice quality was past the threshold of "nobody notices." We were happy with it. Then we had a licensing problem. Fish Speech's license is restrictive for commercial use. We were publishing 200 narrated blog posts a month on a model we couldn't fully commercialize. That needed to change. So we tested alternatives. The obvious move was Mistra
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Why I chose Unsloth (before training a single token)
Honest note up front: I have not yet fine-tuned anything with Unsloth. I have not run a single training job. What I did is spend three weeks researching fine-tuning frameworks before writing a line of training code — and at the end of that research, I picked Unsloth and committed to it. This post is about why. I'm writing it now, before I start, for two reasons. First, so that if this decision ages badly I have to own it public
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You might not have read this
A couple of older essays we think are worth a second look.
I Almost Paid $4,000 a Year to Rent My Own Voice
I almost paid $4,000 a year to rent my own voice back to me. ElevenLabs. $330/month. The model that powers it? Open weights. The inference? Runs on 3GB of RAM. The voice cloning? A 30-second sample and a model you can download for free. The only thing between you and the exact same output is a setup guide nobody bothered to write. So I wrote one. Then I open-sourced it. The gap The gap between what AI costs to run and wha
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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
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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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