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“Even a poor man feels like a king when he marries the right woman.” — African proverb
Janty@CFC_Janty
Since Dembele got married, life kept getting better for him.
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$WULF has guided 250-500 MW per year in leased critical IT delivery. I am expecting a bump in this guidance and they are trending closer to 750 MW per year with their development sites.
By end of this year, 522 total MW should be operational.
Here's what future years looks like:
2027
384 MW Justified Data
162-242 MW Lake Mariner
84 MW Abernathy JV Option
2028
400 MW Muskie Data
120 MW Lake Hawkeye
2029
500 MW Chesapeake Data
200 MW Lake Hawkeye Ph 2
2030
400 MW Muskie Data Ph 2
Now, this does not include any additional generation at LM, Hawkeye, or Justified and the team is not done adding more sites. Future looks bright.
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Larry Ellison, the man who built Oracle into a $500 billion enterprise software empire and he said something that every investor needs to hear (Save this).
"By 2029, I can guarantee you, AI is not going to be the problem."
The problem is going to be compute specifically, who has enough of it and who does not.
Ellison described the current AI race in terms that strip away all the abstract commentary about models and capabilities and reduce it to the one thing that actually determines who wins: "Me and Elon begging Jensen for GPUs. Please take our money. We need you to take more of our money, please."
Citigroup raised its forecast for AI infrastructure spending to $2.8 trillion through 2029, with hyperscalers already spending at a $490 billion annual rate by end of 2026 and the firm estimates global AI compute demand will require 55 gigawatts of new power capacity by 2030 at a cost of approximately $50 billion per gigawatt.
Sam Altman publicly thanked Jensen Huang this past March for significantly increasing NVIDIA's capacity at AWS, the CEO of the most important AI lab in the world writing a thank you note to the chip supplier because compute is still the binding constraint on everything OpenAI wants to build.
Ellison's point about getting there first is the part of this clip that deserves a second read.
He named three specific races, self-driving, reading cancer biopsy slides, and synthesizing video and said that being first in each one is a big deal.
The logic is that in winner take most AI markets, the first mover trains the best model, the best model attracts the most usage, the most usage generates the most data, and the most data trains the next best model, a compounding loop that the second-place finisher never catches up to.
"The guys in this race are very smart and they understand they need to be best at something," Ellison said.
What makes this clip so important right now is the timing.
The AI GPU chip market is projected to grow at a 32.4% CAGR through 2029, reaching $145 billion in incremental spend, and NVIDIA's data center revenue is already running at a pace that would have seemed impossible three years ago.
Every major hyperscaler, Microsoft, Amazon, Google, Oracle, Meta is no longer funding AI capex from operating cash flows alone, they are borrowing to keep up, because falling behind in compute now means ceding the winner-take-most race Ellison just described.
At Milk Road, we have been positioned in NVIDIA, AVGO, AAOI, MU, and Bloom Energy and more.
Come join Milk Road Pro and get the full picture on how we are playing every layer of the GPU demand supercycle that Larry Ellison just guaranteed will not slow down before the end of the decade, link below/bio.
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