Why training needs datacenters
The idea: Cut the model into slices, put one slice per GPU, and wire them together to act as one machine.
What you'll be able to do: You can explain why frontier training needs datacenters: models are split across many GPUs.
The problem it solves: A frontier model won't fit on one GPU, and needs enormous compute.
Builds on: Why GPUs beat CPUs, Scaling laws
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