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Models are fixed. They do not learn post training.

Which means that training needs to be ongoing. So the revenue covers the inference? So what? All that means is that it doesn't cover your costs and you're operating at a loss. Because it doesn't cover the training that you can't stop doing either.

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Training costs are fixed. Inference costs are variable. The difference matters.

No they are not. They are exponentially increasing. Due to the exponential scaling needed for linear gain. Otherwise they'd fall behind their competition.

Fixed cost here means that the training costs stay the same no matter how many customers you have - unlike serving costs which have to increase to serve more people.

Yet somewhere above you said:

>Training costs are fixed at whatever billions of dollars per year.

Which I think is the part people disagree with.


I used the word "fixed" there to indicate that the cost of training is unaffected by how many users you have, unlike the cost of serving the model which increases as your usage increases.



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