“When they can perform a task, AIs are much cheaper than humans” by djbinder

AI systems are increasingly capable of substantial work. I'm old enough to remember 2025, when METR's time-horizon graph climbed from seven-minute tasks at 80% reliability at the start of the year to tasks taking more than an hour by the end. The time horizons for Astra and Fable 5.1 are now so long that METR's current task suite cannot reliably estimate them. But the recent Hugging Face attack and a slew of mathematics results show that frontier systems are now capable of some tasks that would take months or years of human effort.

Sure, AIs have now solved a Millennium Prize problem, but at what cost? Doing a task is not the same as doing it cheaply. AI systems will only replace human workers if running them costs less than paying the workers. Perhaps these feats are expensive, so that even once AI can do the work, compute limits how many workers it replaces. But if AI systems are already cheap and AGI really is a few years away, we could soon be living in a world with vast numbers of digital workers, which could threaten not only our jobs but also our continued control over the future.

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Outline:

(01:18) The data

(03:17) Costing FLOPs

(05:05) Implications for AGI costs

(07:51) How many AGI workers?

(11:12) How much cheaper could AI get?

(13:39) Training compute

(16:54) Appendix A: Methodology

(20:50) Appendix B: how much learning does a trained model embody?

(22:20) Domains of knowledge

(24:20) Facts

The original text contained 11 footnotes which were omitted from this narration.

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First published:
September 27th, 2026

Source:
https://www.lesswrong.com/posts/zPiQqQ6JJn6ysPpKW/when-they-can-perform-a-task-ais-are-much-cheaper-than

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Narrated by TYPE III AUDIO.

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