> Given the trajectory of inference cost, it unlikely that they would fail to reach profitability.

Is there evidence that their revenues are growing faster than their costs?

versteegen 2 days ago | parent | next [-]

The place to go for those numbers is https://epoch.ai/data/ai-companies

Very little data about expenses, but it looks like they may be growing a little slower (3-4x a year) than revenue. Which makes sense because inference and training get more efficient over time.

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lumost 3 days ago | parent | prev [-]

We don't have evidence one way or the other. But from the public statements the idea that they lose roughly their revenue seems constant over time. It's possible that that is simply a psychological barrier for investors. Meaning they grow their losses at roughly 2x their revenue growth rate.

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vel0city 3 days ago | parent [-]

> Given the trajectory of inference cost, it unlikely that they would fail to reach profitability.

> We don't have evidence one way or the other

I don't see how both of these things can be true. How can we know something to be likely or unlikely if we have no evidence of how things are?

If we don't have any evidence they're moving towards profitability, how is it likely they will become profitable?

	▲	lumost a day ago \| parent [-]
		Growing businesses tend to consume capital. How much capital is appropriate to burn is subjective, but there are good baselines from other industries and internal business justifications. As tech companies burn capital through people time, it's hard to directly figure out what is true CapEx vs. unsustainable burn. You wouldn't demand that a restaurant jack prices up or shutdown in its first month of business after spending ~1 MM on a remodel to earn ~20k in the first month. You would expect that the restaurant isn't going to remodel again for 5 years and the amortized cost should be ~16k/mo (or less).