@rohanpaul_ai: 100% agree. That famous Stanford report already found GPT-3.5-level inference costs has already fallen 280X in under 2 …

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Summary

A discussion on how rapidly falling inference costs (280X for GPT-3.5-level in under 2 years) will lead to Jevons paradox, driving far more demand for AI and making multi-agent systems ubiquitous with cheaper open-source models.

100% agree. That famous Stanford report already found GPT-3.5-level inference costs has already fallen 280X in under 2 years. And so we will see Jevons paradox for intelligence: cheaper inference will create far more demand. Multi-agent systems will be everywhere when we have Opus 4.8 class open-source model at 4X cheaper prices.
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Cached at: 07/11/26, 03:26 PM

100% agree.

That famous Stanford report already found GPT-3.5-level inference costs has already fallen 280X in under 2 years.

And so we will see Jevons paradox for intelligence: cheaper inference will create far more demand.

Multi-agent systems will be everywhere when we have Opus 4.8 class open-source model at 4X cheaper prices.

yess, that has happened over the last 2 years (by 280X), and will happen in the next 2 years as well

@rohanpaul_ai totally see this happening. cheaper inference is gonna make AI tools even more accessible. curious how it’ll change the job market in a couple years tbh

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@AriX: Loved this piece.

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Dan Shipper reports that despite automating everything possible with AI agents, his company has grown from 4 to 30 human employees since GPT-3, arguing that AI makes expert competence cheap and drives up demand for human work.