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Briefings and ideas about AI investment from AI podcast discussions and the research they cite, with links to the original sources.
Critic Ed Zitron predicts OpenAI runs out of cash in 2027, with losses spreading to SoftBank, Oracle, cloud giants and index-linked retirement savings. Amazon's Andy Jassy says its capital spending is backed by customer commitments.
Economist Steve Keen argued that the sheer cost of frontier AI and the physical resources it needs may be what slows the race, and forecast that the one company left standing will be Chinese rather than American.
Alvin Wang Graylin, speaking personally on Moonshots, says US–China AI talks need not reach a solution on day one and should start with an emergency hotline, shared safety tests and agreement to keep talking.
Alvin Graylin argues cheaper open models and local computing could erode the cloud revenues that AI data center debt relies on, likening NVIDIA's plan to mobilize over $500 billion in outside financing to subprime lending, as a warning, not proof.
Ramez Naam says AI demand could finance multi-plant nuclear orders that may lower costs, but doubts small reactors can supply power within the five-year window he sees as predictable, and expects their roughly 2030 schedules to slip.
Ramez Naam estimates space-based AI could compete on cost if launch prices fall to a quarter to a tenth of current levels, a rough guess. He says building and launching enough hardware, with permits and reliability, is a separate hurdle.
Ramez Naam passed on Panthalassa's early Bitcoin pitch but has since invested in its wave-powered, seawater-cooled ocean AI computers. Its 2-cent/kWh power cost is a target; northern-Pacific pilots are planned for 2026.
Energy investor Ramez Naam argued AI data centers could connect to the grid sooner by cutting power use at peak times through job scheduling or batteries, though national spare-capacity estimates don't guarantee power at any site.
NVIDIA signed memorandums with six financial firms aiming to mobilize over $500 billion for customers' AI infrastructure. On Moonshots, panelists debated whether GPUs can back long-term financing before newer chips undercut their earnings.