AI data center buildouts already rival the Manhattan Project in scale, but there’s little public info about them.
So we spent the last few months reading legal permits, staring at satellite images, and scouring news sources.
Here’s what you need to know. 🧵
So we spent the last few months reading legal permits, staring at satellite images, and scouring news sources.
Here’s what you need to know. 🧵
AI data centers will be some of the biggest infrastructure projects in history
e.g. OpenAI’s Stargate Abilene will need:
- As much power as Seattle (1 GW)
- >250× the compute of the GPT-4 cluster
- 450 soccer fields of land
- $32B
- Thousands of workers
- 2 years to build
e.g. OpenAI’s Stargate Abilene will need:
- As much power as Seattle (1 GW)
- >250× the compute of the GPT-4 cluster
- 450 soccer fields of land
- $32B
- Thousands of workers
- 2 years to build
By the end of the year, AI data centers could collectively see >$300 billion in investment, around 1% of US GDP.
That’s bigger than the Apollo Program (0.8%) and Manhattan Project (0.4%) at their peaks.
That’s bigger than the Apollo Program (0.8%) and Manhattan Project (0.4%) at their peaks.
Only a few countries have enough power to build many >1 GW data centers like Stargate
E.g. 30 GW is ~5% of the US’ power, ~2.5% of China’s, but ~90% of the UK’s
Other countries can build some frontier data centers and grow their power capacity — but they need more time/money
E.g. 30 GW is ~5% of the US’ power, ~2.5% of China’s, but ~90% of the UK’s
Other countries can build some frontier data centers and grow their power capacity — but they need more time/money
So power is the core determinant of where AI data centers are built.
Other factors like latency matter surprisingly little — it takes >100× longer to generate model responses than transmit data from Texas to Tokyo.
Even serving LLMs from the Moon may not be a big latency issue!
Other factors like latency matter surprisingly little — it takes >100× longer to generate model responses than transmit data from Texas to Tokyo.
Even serving LLMs from the Moon may not be a big latency issue!
Where does this power come from?
Usually a mix of on-site fossil fuel generation and interconnection to the grid.
E.g. Stargate Abilene will start off with on-site natural gas, then connect to the grid to access Texas’ abundant renewable power.
Usually a mix of on-site fossil fuel generation and interconnection to the grid.
E.g. Stargate Abilene will start off with on-site natural gas, then connect to the grid to access Texas’ abundant renewable power.
This power runs IT equipment on “server racks” with a small area of 0.5 m^2. But each rack uses enough power for 100 homes!
This means a huge amount of heat in a small space. So you can’t cool these chips with fans — you need liquid coolants to efficiently soak up the heat.
This means a huge amount of heat in a small space. So you can’t cool these chips with fans — you need liquid coolants to efficiently soak up the heat.
3 implications for AI policy/impacts:
1) AI’s climate impact has been small so far.
For example, AI data centers use 1% of US power vs 8% for lighting and air conditioning (12%).
But if trends continue, this could change in the next decade.
1) AI’s climate impact has been small so far.
For example, AI data centers use 1% of US power vs 8% for lighting and air conditioning (12%).
But if trends continue, this could change in the next decade.
2) AI data centers are growing fast enough to support 5×/year growth in frontier training compute.
So companies probably won’t need to decentralize AI training over the next 2 years.
However, in practice they might choose to anyway, e.g. to soak up excess power in the grid.
So companies probably won’t need to decentralize AI training over the next 2 years.
However, in practice they might choose to anyway, e.g. to soak up excess power in the grid.
3) Thousands of people from multiple parties build >1 GW data centers, and cooling infrastructure can be spotted using satellite imagery.
So unlike the Manhattan Project, AI data center buildouts are hard to keep secret from the rest of the world.
epoch.ai/data/data-cent…
So unlike the Manhattan Project, AI data center buildouts are hard to keep secret from the rest of the world.
epoch.ai/data/data-cent…
Much more in the post!
The post was written by @ansonwhho, @benmcottier, and @YafahEdelman.epoch.ai/blog/what-you-…
The post was written by @ansonwhho, @benmcottier, and @YafahEdelman.epoch.ai/blog/what-you-…
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