Under US GAAP, production costs are capitalized when they're incurred and then amortized into cost of revenue over the period when the content actually earns revenue. Because content usually earns more revenue early and then tapers off, the amortization is usually front-loaded.
The one problem with this is that not all training actually goes into what's sold to customers. There are experiments, failed runs, various studies, etc. So you would need to come up with a way to cost only the final production run (and perhaps post-training) to come up with a number akin to content cost.
ASC 730 basically favors expensing anything uncertain, so unless you have a really good, defensible way of breaking out these costs and separating them, doing it this way would go against the current accounting standards.
Would this be analogous to, say, paying lower level employees to read endless scripts and write coverage, purchasing some of those scripts, producing but then canning failed pilots, etc. obviously some of this is outdated, but I’m at least thinking more of the pre-streaming era of television production pipelines, in which there certainly was a non trivial amount of content produced that never reached consumers.
Thanks for your more detailed response; I obviously know nothing about the real intricacies of GAAP so it’s interesting to understand the analogues better.
If you bought a script, that would be capitalized as an asset, and written off if abandoned. And so on.
The difference is that film and TV have an industry-specific standard (ASC 926). AI companies fall under the general R&D and software rules and those don't allow capitalization when there's significant uncertainty about whether or not the project will work. There's a new software standard (ASU 2025-06) that makes this explicit with a "significant development uncertainty" test. Because you don't know the outcome of a model training run until it's done the training costs are generally expensed as they are incurred.
Obviously there's room to debate whether the rules should be updated and maybe they will be in the future. But they are what they are now. Expensing model training as R&D isn't an accounting choice companies like Anthropic have made on their own. It's what the rules require. So obviously, understanding what the rules are and where different costs show up on the financial statement, it's clear that inference gross margin alone doesn't speak to whether the business is ultimately viable. But the high inference gross margins shouldn't be dismissed as meaningless or the product of some sort of accounting trickery either.
No problem if this is so far off topic as to no longer be interesting to you… I just don’t often engage with somehow who can comment on Hollywood accounting with actual knowledge of relevant standards!
There's a formal process for these rules to be made and it's designed to be responsive to the needs/requests of businesses, investors, auditors, etc. While I wouldn't say there's any room for differences of opinion, given the rule-making process, I don't think there are any fist fights taking place over these. :)
Isn’t it plausible that this is conceptually wrong? What if a model’s revenue-generating potential only lasts for something like a year due to, loosely speaking, competition? Doesn’t this make model development more akin to, say, the costs of annual agricultural planting/harvesting/delivery cycles, or a tv network’s annual (back in the day at least…) production cycle for its main content?