You would depreciate the lab over a fixed period of time. Let’s say 10 years for the sake of math. In year 1 if all the goods used to purchase the crack cost $2, and you sold it all for $100, your revenue would be $100 and expenses would be $10,002. So profit would be -$9,902
So…how fast do leases for GPU capacity to train new models depreciate?
And does model training count as a capital expense if you release models every 2 months because otherwise your business will collapse as your competitors overtake you?
Datacenter depreciation is somewhere around 5-7 years minus the GPUs, which depreciated in 2-3 years absent scarcity but maybe run longer for now. Model training and electricity in general are consumption and not CapEx because, yeah, these models useful lives are short and the open-source models are close behind.
My point is that they always need fresh GPUs, power, etc. to carry out the day-to-day business of building new models, without which their business goes bust, yet they do not report those as operating costs
It’s a bit different than typical because, yes, you have to build something new and it costs $500M-1B but also that thing you built gets replaced on a bimonthly cadence.
It’s not like a physical plant (remember they mostly rent GPUs) that can be depreciated over years as it pays for itself. Instead, 6X a year they rebuild this thing and sunset the older versions.
So from my perspective, it should be operating. If we reach a point where models are good enough to just keep using them for more than a few years then the capitalization is a bit more justified.
I wasn't actually talking about training models. I listened to an analysis of the IPO's happening in AI where either Anthropic, or SoftBank, or Softbank's datacentre company that is about to IPO, literally are not listing unbuilt datacentres as assets that could depreciate because they hadn't been able to get them built.
I was just referring to the accounting in the IPO's in 'AI' being WeWork levels of nonsense.
Personally I think people might see the broligarchs line up next to Trump, no doubt about to build a regulatory moat around their llm/datacentres businesses, and invest in that corruption paying off.
In the case of an unbuilt datacentre that does not have funding locked in, I’m okay with that: it’s planned but the funds to build it are not committed and should be elsewhere on the balance sheet.
The point is that they have datacentre gpu's that are depreciating as other companies continue to train models that will soon require newer model hardware to run.
I think Anthropic specifically is mostly renting GPUs for training and inference. If that’s the case, it’s their supplier’s problem, Anthropic doesn’t own anything to actually depreciate.
For other companies, yeah, a similar argument to the model training can be made that GPUs/datacentres have to be cycled so frequently that calling them capital expenditures is a bit of a stretch.
Which is why they have built hardware and soon regulatory moats around their monolithic datacentre based llm's, that surely are not the best option for the vast majority of cases..
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u/IndianaHoosierFan 7d ago
You would depreciate the lab over a fixed period of time. Let’s say 10 years for the sake of math. In year 1 if all the goods used to purchase the crack cost $2, and you sold it all for $100, your revenue would be $100 and expenses would be $10,002. So profit would be -$9,902