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How the US and China Could Verifiably Slow AI
Verifiable international AI treaties may depend on hardware-based compute governance rather than unilateral national restrictions.
What: The article outlines methods for enforcing an AI slowdown, including satellite-based remote sensing, on-site semiconductor inspections, and 'guarantee processors'—chips designed to report compute usage and location securely.
Why it matters: Unilateral pauses are strategically suicidal because of the race dynamics between the US and China; verifiable international agreements are viewed as the only way to pace development without losing relative power.
Deep dive
- Unilateral AI slowdowns fail because rivals catch up within a year.
- Compute governance is the primary lever due to concentrated supply chains and predictable scaling laws.
- Proposed enforcement includes cryptographic chip licensing and cluster size caps.
- Hardware-based 'guarantee processors' could enforce treaty rules via tamper-resistant environments.
- Remote sensing can detect large-scale compute signatures but struggles with small-scale violations.
Decoder
- FLOPs (Floating Point Operations): A standard measure of compute performance used to track AI training intensity.
- Guarantee Processor: A theoretical hardware module added to compute units to enforce rules and report telemetry without exposing model secrets.
Original article
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