Compute Thresholds

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  "llmSummary": "Comprehensive analysis of compute thresholds (EU: 10^25 FLOP, US: 10^26 FLOP) as regulatory triggers for AI governance, documenting that algorithmic efficiency improvements of ~2x every 8-17 months threaten to make static thresholds obsolete within 3-5 years. Training costs range from \\$7-10M at 10^25 FLOP to \\$70-100M at 10^26 FLOP, with only 5-15 companies globally currently captured. Identifies key evasion strategies (distillation, jurisdictional arbitrage, inference scaling up to 10,000x) and provides quantified forecasts showing absolute thresholds will capture 100-200 models by 2028 versus 14-16 for relative thresholds.",
  "description": "Analysis of compute thresholds as regulatory triggers, examining current implementations (EU AI Act at 10^25 FLOP, US EO at 10^26 FLOP), their effectiveness as capability proxies, and core challenges including algorithmic efficiency improvements that may render static thresholds obsolete within 3-5 years.",
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