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⚠️ Bigger clusters matter, but fragmentation is dangerous Robin also warns against the "small blast furnace" trap: trying to build frontier models with scattered, undersized clusters. For large model training, cluster size is a hard constraint. A large cluster can always use only part of its capacity. A small cluster runs into limits that cannot be wished away. So the industry impact is not just technical. It is organizational: serious frontier training may require concentrating domestic compute, not spreading it too thinly.