The Constraint Nobody Prices
Compute gets the headlines; the network decides whether the headlines are true. A GPU is only as useful as the data it can be fed and the peers it can talk to. When people say a model was trained on tens of thousands of accelerators, they are describing a communications feat first and an arithmetic feat second. Faraday's read: the market has learned to count chips. It has not yet learned to count the fabric between them. That gap is where the next decade of surprises lives.
Knowledge check
Why is it misleading to describe an AI cluster purely by its accelerator count?
Show the answer
Because a cluster's useful throughput depends on how fast the accelerators can exchange data. If the interconnect cannot move gradients and activations between chips quickly enough, most accelerators sit idle waiting on the network. Chip count sets a ceiling; the network determines how much of that ceiling is reachable.