According to @ylecun, who amplified economist Steve Rattner’s chart, U.S. federal debt held by the public is projected to reach 156% of GDP by 2050 and past projections have typically undershot reality, as reported by Steve Rattner on X and highlighted on Morning Joe. According to Steve Rattner’s post on X, rising debt trajectories imply greater fiscal pressure that could tighten public R&D budgets and tax incentives, directly affecting AI research funding, data center subsidies, and semiconductor incentives. As reported by Morning Joe via Steve Rattner’s chart, prolonged deficits could raise borrowing costs, pressuring AI startups with capital-intensive GPU procurement and long payback cycles, while advantaging cash-rich hyperscalers in compute buildouts. According to the shared source on X, executives should plan for scenario-based financing, prioritize unit economics for inference at scale, and explore partnerships for shared GPU clusters to mitigate higher cost of capital. As reported by Steve Rattner on X, if projections continue to be revised upward, AI firms should stress test models for cloud egress fees, energy price sensitivity, and delayed public grants, while enterprise buyers may shift toward cost-optimized model distillation and on-prem accelerators to control total cost of ownership.