AI training costs are increasing around 3x annually across each of the last 8 years to achieve its performance improvements. Last year, spending across all labs was $150bn. Keeping the 3x trend means that, to keep pace with current advances, costs should rise to $450bn in 2025, $900bn in 2026, $2.7tn in 2027, $8.1tn in 2028, $25tn in 2028, and $75tn in 2029 and $225tn in 2030. For reference, the GDP of the world is around $125tn.

I think the labs will be crushed by the exponent on their costs faster white-collar work will be crushed by the 5% improvement exponent.

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Collisteru 6 days ago | parent | next [-]

Be careful you're not confusing the costs of training an LLM and the spending from each firm. Much of that spending is on expanding access to older LLMs, building new infrastructure, and other costs.

	▲	OtherShrezzing 6 days ago \| parent [-]
		That’s a fair criticism of my method, however model training costs are a significant cost centre for the labs. Modelling from there instead of from total expenditure only adds 2-3 years before model training costs are larger than the entire global economy.

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johnnienaked 6 days ago | parent | prev | next [-]

Your math is a bit less than it should be because you doubled instead of trebled 2026

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pkaye 6 days ago | parent | prev [-]

The current trained models are already pretty good enough for many things.

	▲	utyop22 6 days ago \| parent \| next [-]
		Is that so? Ok let the consumers decide - increase the price and let's see how many users are willing to pay the price.
	▲	amlib 6 days ago \| parent \| prev [-]
		They are mediocre plagiarism machines at best.