Follow the Power: Betting on AI's Infrastructure Backbone
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Hey,
Ever feel like tech news is written in code?… well… we came across a newsletter that translates the chaos of tech into plain english, Thoughts From The DataFront… It takes big ideas and rewrites them into practical insights you can actually use.
I'll let Thoughts From The DataFront take over from here...
"The thing that will gate us the most is power. It’s the biggest strategic constraint…We might run out of money before we run out of silicon.” warns Martin Lund, EVP of Hardware at Cisco.
Training AI is becoming astronomically expensive. Models like GPT-4 and Gemini Ultra cost $40M and $30M respectively, just for training runs. CEO of Anthropic, Dario Amodei, has stated that AI developers are likely to spend close to a billion dollars on a single training this year, and up to ten billion dollars training in the next two years
Based on new research by Cottier and Rahman (2024), training costs for frontier AI models have grown 2.4x annually since 2016.
These costs break down into:
Hardware (Chips & Computers): 47-65%
Brain Power (R&D staff): 29-49%
Energy: Currently 2-6%, but this seemingly small number hides a bigger problem
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Why This Matters
Gemini Ultra already requires 35 megawatts - enough to power 25,000 homes. By 2029, AI training could require up to 1 GW. To put this in context, the top ten largest power plants in the United States have a capacity ranging from 3 GW to 7 GW
The Investment Thesis
Just as railroads and utilities powered the Industrial Revolution (see “The Upside of Tech Bubbles: Building Tomorrow's Infrastructure”). AI needs its own infrastructure backbone: data centers and a massive power supply. Instead of betting on which AI company wins, invest in what they all need to operate.
Investment Strategy: "Pick and Shovel" Play
Four Foundation Builders*:
NextEra Energy (NEE): Top renewable energy provider in anticipation of significant electricity demand growth from AI
Brookfield Renewable (BEP): Global clean energy partner, directly supporting AI infrastructure power needs
Digital Realty (DLR): Leading AI-ready data center provider
Vertiv (VRT): Specialized cooling solutions for high-density data centers, essential for managing AI computational heat generation
Just like the railways before them, these companies are critical for tomorrow's essential infrastructure. They may not make headlines like OpenAI or Anthropic, but they're providing the foundation these AI giants need to operate.
*key risks to monitor: Potential regulatory challenges, competition from new infrastructure providers, and breakthroughs in AI efficiency that could alter the trajectory of infrastructure needs.
Note: This analysis is based on current research and market conditions. Always do your own research before making investment decisions.
Those are my Thoughts From the DataFront
Max
More charts from the research report (if you are nerdy like me)
source: https://arxiv.org/pdf/2405.21015v1
Nothing in this email is intended to serve as financial advice. Do your own research. See important disclaimer & terms of service.
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