Thats like saying a restaurant is profitable because they're making money selling meals if you ignore the costs of ingredients.

Of course they are profitable if you ignore their cost to bring a product to market.

The problem with that comparison is restaurants largely don’t have much room to adjust price or optimize cost. The AI industry is too new with many unknowns right now so investors are willing to take risk. For the hyperscalers the bet is that being left out is going to be a greater loss than overbuilding.

That’s the wrong analogy. Model training is more like the setup costs of developing the menu and training staff. What’s driving the costs is important when talking about financial sustainability. If it’s mostly coming from optional R&D investments instead of the direct costs of producing the food then you can simply not exercise the option and be profitable. If it’s more coming as a variable cost that scales with each meal served that’s a very different situation.

Yeah it should be factored in, but it’s a different set of implications for long term sustainability. They don’t actually need to test and optimize a new menu every day or week. If they decide to just stick to the same one longer they can get way more return from each dollar spent on development. It’s just that right now the rate of improvement you get with training is really high and nobody can afford to fall behind their competition.

These companies are continually training new models. This is not a long term amortized cost, it's actual COGS.

Yeah, sure you can ignore the cost of purchasing the building for the restaurant for most profitability calculations, but if every year or two you were tearing down your old building and building a new one, you better believe that has to be in your profitability calculations.

I think the relevant question to define the counterfactual is what would happen if they stopped training.

If you can simply not remodel your restaurant and keep making money, then yeah, it makes sense to call it profitable.