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• @david_chisnall@infosec.exchange 2026-09-30 09:46

  @troberts@theblower.au @luciedigitalni@aus.social There's no good path for them. They have two costs: training and inference. Training corresponds to capital expenditure (capex): you do it once and then try to amortise it across uses. Inference corresponds to operational expenditure (opex), which you pay each time. This leads to a 2x2 matrix of possibilities with each of them either going down or staying high (I'm going to treat 'getting more expensive' as is happening with the capex as equivalent to 'staying infeasibly high'). Note: Oversimplifications follow: Typically, successful growth businesses are ones with high capex (makes it hard for new companies to enter the market) and low opex (means that the bigger they are, the more profit they get). Boutique businesses are the other way around: they have high opex and customers who are willing to pay a premium. Commodity businesses are low capex and low opex: margins tend to low, it's easy for new competitors to enter the market and this pushes the margins lower. Almost no successful businesses have both high opex and capex and that's where current LLM vendors are. So let's look at those options. Capex stays high, opex gets low. This is probably the best outcome. Growing the number of customers lets you amortise the capex and so there's a path to profitability. Unfortunately, this also means running inference over cheaper Chinese models will be cheaper and so you need to have models that can do something that the cheaper ones can't do. Your moat is largely gone. Fine for LLMs in general, bad for OpenAI and Anthropic (and anyone else who wants to recoup their ludicrous investment). Note that recent gains in utility have come from doing a lot more work during inference, so this is quite unlikely. Capex stays high, opex stays high. This is basically the status quo. Each new customer loses you more money. If you put up your prices, you lose customers and so the capex dominates. If you lower prices, opex dominates. No win. Capex gets low, opex gets low. In this case, offering LLM services is easy to make profitable but now you're a commodity market. Existing vendors have no moat. New models get trained cheaply. LLMs survive as a technology but anyone with large sunk costs is in a bad place because they can't compete with new vendors. Capex gets low, opex stays high. This one is a bit weird. You have low fixed costs to amortise but you are losing money on each customer. Adding more customers makes you less profitable, so the only path is to put prices up. This may lead to profitability, but also a smaller market. If you're selling investors a story that you're a growth company, this doesn't work: your current customer base is an upper bound on your future number of customers, because you're going to lose some when you put prices up.

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