Why Ahamed Sees 1873 in Today’s AI Boom

AI summary

How does Ahamed compare the two booms? Liaquat Ahamed calls 1873 a fairly good analogy for today’s AI and data-center boom, while stressing that every boom-bust cycle is different and that the comparison also has elements in common with 1929. He says the central shared risk is overbuilding financed by debt. Data-center construction has increasingly relied on opaque debt financing as technology companies’ resources have proved insufficient. (evidenceIndex: 0, 5; 20:28 and 45:52) What warning signs does he identify?

Ahamed highlights excess capacity, eroding profitability, and financing constraints. He compares declining railroad profitability by 1873 with the possibility that data-center construction could push down the prices of AI tokens, which are already falling. He also points to local opposition, difficulty measuring data-center output, and uncertainty about whether demand for tokens is inexhaustible. (evidenceIndex: 1, 2, 4; 22:04, 23:27 and 33:02) Why might overbuilding happen despite caution? According to Ahamed, individual railroad and technology companies may try to act carefully, but each may fear losing market share by slowing construction.

Their collective decisions can therefore produce overbuilding, which he says would require collective action to prevent. He describes the current market as definitely in a manic phase, although he cannot determine precisely where it is in the cycle and says it could continue for another year or two. (evidenceIndex: 3, 6; 24:51 and 51:13) How could an AI crash resemble the railroad crash? Ahamed says a major AI player could face financing problems and become unable to raise capital. He also identifies possible competitive pressure from open or Chinese models that could sharply erode profitability, along with geopolitical risks.

The source does not establish that any of these events will occur. (evidenceIndex: 7; 52:24) Taken together, Ahamed’s comparison rests on overbuilding, weakening profitability, and financing pressure, while he explicitly cautions that the analogy is not exact.