There's no moat, and they have to work even harder.
Competition is good.
Competition is good.
Their value-prop (moat) is that they've burnt more money than everybody else. That moat is trivially circumvented by lighting a larger pile of money and less trivially by lighting the pile more efficently.
OpenAI isn't the only company. The Tech companies being beaten massively by Microsoft in #of H100s purchases are the ones with a moat. Google / Amazon with their custom AI chips are going to have a better performance per cost than others and that will be a moat. If you want to get the same performance per cost then you need to spend the time making your own chips which is years of effort (=moat).
DeepSeek has proven that the latter is possible, which drops a couple of River crossing rocks into the moat.
Google with all its money and smart engineers was not able to build a simple chat application.
It seems they have high quality trainingsdata. And the knowledge to work with it.
... is definitely something I've said before, and recently, but:
> That moat is trivially circumvented by lighting a larger pile of money
If that was true, someone would have done it.
The deepseek paper states that the $5mil number doesn't include development costs, only the final training run. And it doesn't include the estimated $1.4billion cost of the infrastructure/chips Deepseek owns.
Most of OpenAI's billion dollar costs is in inference, not training. It takes a lot of compute to serve so many users.
Dario said recently that Claude was in the tens of millions (and that it was a year earlier, so some cost decline is expected), do we have some reason to think OpenAI was so vastly different?
Inference capex costs are not a defensive moat as I can rent gpus and sell inference with linear scaling costs. A hypothetical 10 billion dollar training run on proprietary data was a massive moat.
https://www.itpro.com/technology/artificial-intelligence/dol...
I find huge value in these models as an augmentation of my intelligence and as a kind of cybernetic partner.
I can't think of anything that can actually be automated though in terms of white collar jobs.
The white collar model test case I have in mind is a bank analyst under a bank operations manger. I have done both in the past but there is something really lacking with the idea of the operations manager replacing the analyst with a reasoning model even though DeepSeek annihilates every bank analyst reasoning I ever worked with right now.
If you can't even arbitrage the average bank analyst there might be these really non-intuitive no AI arbitrage conditions with white color work.
It is the closed competition model that’s being left in the dust.