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Good morning to everyone who thought the GPU buildout was already loud.
According to Epoch AI, since August 2024 computing capacity inside a single AI data center has doubled roughly every 7 months.
Today, why that line is about to get steeper.
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Epoch measures capacity in H100-equivalents, a way to compare different Nvidia chips against one common yardstick.
The leading facility sat around 100,000 of those units in 2024. By 2026 the frontier is already past one million.
If the same pace holds, Epoch’s chart points toward several million H100-equivalents in a single site by 2028.
The trend band on their plot runs about 3.3x per year.
Colossus, Anthropic-Amazon New Carlisle, Microsoft Fairwater, and Meta Prometheus have taken turns holding the record.
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The push behind that curve is product.
OpenAI is rolling out GPT-6 Astra across ChatGPT, its API, AWS Bedrock, and enterprise plans.
Meta launched Muse, a personal agent that can book appointments, manage projects, and keep working after you leave the app, with distribution through mobile, the web, WhatsApp, and later AI glasses.
A chatbot answer is often one model pass. An agent is a stack of passes.
One user ask can spawn research, tool calls, drafts, checks, and follow-ups before anything lands back in the chat.
That multiplies compute per session even when each individual chip gets more efficient.
Mass distribution multiplies it again.
Astra on ChatGPT and Bedrock, Muse on WhatsApp-scale surfaces, and every rival answering with a bigger Claude or Gemini cluster turns each launch into another round of training, testing, and serving.
More efficient chips and leaner models will cut the cost of a single step. Better products will still pull more users into multi-step work that did not exist when the only job was autocomplete.
Efficiency lowers the price of one action. Agents raise how many actions a person asks for.
So what does this mean for your portfolio?
Keep watching power, chips, and networking ($NVDA, $AVGO, the hyperscalers).
Add a second line item: demand per user.
When one request becomes ten model actions, the data-center doubling clock has somewhere to go. Agent rollouts are the new parameter count.
What pulls the next wave of AI compute first?
That’s it for today!
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