Post #4748053 · Elektrine

2026-09-18 11:16 UTC

The AI infrastructure race also reshapes hardware markets. Demand absorbs advanced packaging and high-bandwidth memory while capacity moves away from conventional components. Shortages and higher prices can spread far beyond AI. Financing adds another layer. Chipmakers and cloud providers invest in AI labs that become major customers. Debt, private credit, long-term commitments, and off-balance-sheet structures fund the buildout. Circular financing may indicate a bubble, but does not prove one. It can make money travel in a circle and return wearing a hat labelled “independent demand,” while spreading failure through a tightly connected system. The BIS calls the macro-financial risk moderate, not absent, and dependent on very high future earnings. That is a huge bet on benefits we still struggle to measure. Unlike a casino, this bet reaches people who never placed a chip and will receive none of the winnings. They can face higher prices, public costs, and economic fallout. 10/34

Replies (1)

@masek@infosec.exchange 2026-09-18 11:17

Then there is duplication. Competing labs acquire similar data, run similar experiments, and spend vast resources training overlapping general-purpose models behind closed walls. Some duplication is valuable: competition, replication, and alternative approaches matter. At this scale, however, secrecy and the race for a temporary lead mean that failures, dead ends, and discoveries are repeatedly paid for in energy, hardware, money, and human work. Competition is useful. Paying several times to rediscover the same wall in private is less obviously so. The final training run is only a fraction of total R&D compute, and much of the search remains invisible. More compute has produced remarkable gains, but a larger invoice is not evidence that the next run will create proportional social value, or even a durable business advantage. For me, the burden of proof rises with the resources committed. 11/34

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