If frontier AI progress shifts from pre-training compute to inference-time compute, AI governance must be rebuilt around deployment-time capabilities and transparency, with different implications depending on whether that inference happens during deployment or inside the training process.
And even if the weights were stolen, the thief would still have to pay the high inference-at-deployment costs
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Inference Scaling Reshapes AI Governance
If frontier AI progress shifts from pre-training compute to inference-time compute, AI governance must be rebuilt around deployment-time capabilities and transparency, with different implications depending on whether that inference happens during deployment or inside the training process.