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Open Weights, Closed System
Google shipped local AI on the Mac this week. The weights are Apache 2.0. The experience is a walled garden. That's not a contradiction. That's the playbook.
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.
Canada Is Renting Its Sovereignty
In the last piece I wrote about the anchor: Canada designated Cohere as its national champion at the foundation model layer — $240 million, a 24-year term, an MOU that called the company "the only sovereign, cloud-agnostic large language model operating in Canada," and a fund Cohere itself proposed. That designation is settled for a generation. This piece is the opposite kind of writing. The last one was analysis of public records, and I tried to stay out of it. This one carries a point of
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How Cohere Wrote the Fund That's Now Funding Everyone Else
On Christmas Eve 2024, the Government of Canada issued a Letter of Intent to Cohere for a Strategic Innovation Fund contribution of $240 million. The timing is the first thing worth noticing. Christmas Eve is when governments send letters they want done quickly and quietly. The Trudeau government was already wobbling. Chrystia Freeland had resigned on December 16, eight days earlier, in a public letter that called out the Prime Minister's "costly political gimmicks." Less than two weeks lat
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Sovereignty Is Not About Ownership
A vice-president at a Canadian university called me last month. Her president had told her the institution needed to be on sovereign AI within the year. The provincial government had announced a funding program. Other universities were already applying. She wanted to know what she should be evaluating. I asked her what sovereign meant in this context. She paused for a long time. Then she said, "I think it means the data stays in Canada." I asked what about it staying in Canada specifically
Read essayFrom the series · 90-Day Action Plan to Surviving AI
The Untethering
"Who are you when the job goes away?"
More on Policy & Economy
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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Sovereignty Is Not About Ownership
A vice-president at a Canadian university called me last month. Her president had told her the institution needed to be on sovereign AI within the year. The provincial government had announced a funding program. Other universities were already applying. She wanted to know what she should be evaluating. I asked her what sovereign meant in this context. She paused for a long time. Then she said, "I think it means the data stays in Canada." I asked what about it staying in Canada specifically
Read essayWhile 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
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A couple of older essays we think are worth a second look.
When to Build vs Buy in AI (My Edition)
I've gotten this wrong before. Not in a small, low-stakes, "oops we picked the wrong software" kind of way. In a way that cost me a year of my life, hundreds of thousands of dollars, and nearly killed a business. So when I tell you the build vs buy question in AI is the most important decision a founder can make right now, I'm not being dramatic. I'm speaking from the scar tissue. The Year I Built What I Should Have Bought
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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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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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