regulatory-capture
5 articles
- Anthropic's $2 Trillion IPO Rests on a Profitability Metric That Excludes Its Largest Costs
Anthropic's >80% "gross margin" and $559M "adjusted operating profit" exclude partner revenue sharing, training costs, and stock-based compensation. The S-1 discloses $518B in take-or-pay compute obligations, 80% non-cancelable, with named counterparties including Broadcom ($161B), Google ($111B), and Amazon ($110B). The safety slowdown is a capital preservation maneuver timed to the IPO window.
- The AI Safety Narrative as a Synthetic Moat
Frontier AI labs face rapid algorithmic depreciation and escalating compute costs. Safety regulation can create a synthetic moat by imposing fixed compliance costs that favor incumbents over open-weight competitors.
- How AI Safety Became a Rent-Seeking Institution
AI safety has increasingly become an institutional apparatus optimized for funding, prestige, regulatory influence, and adoption rather than binding constraint. Material AI risks arise from deployed socio-technical systems, requiring layered governance across compute, security, incentives, organizations, and institutions.
- FDA Regulatory Capture: PDUFA Funding, AI Bypass, and the Speed-Safety Tradeoff
Faster FDA approvals reflect both scientific progress and structural pressure. PDUFA funding, discretionary review shortcuts, and the 510(k) pathway reveal where better methods end and reduced evidence begins.
- The Compliance Bifurcation: Where Regulatory Complexity Creates Real Moats and Where It Does Not
Compliance infrastructure is splitting into a compressing cost-center layer and a small number of rent-extracting moat layers. The barbell is forming at the data-network edge and the regulator-interface edge, while the middle of the stack commoditizes.