> The reported 2025 figures include $7.5 billion in cost of revenue, $19.18 billion in research and development, $5.73 billion in sales and marketing, and $1.57 billion in general and administrative expense
Does training of new models go into RnD or cost? And subscription plans' subsidies, are those cost or sales and marketing?
Pretty likely R&D, but obviously would need to be confirmed by OpenAI.
The original reporting includes this:
> The documents revealed how much OpenAI paid Microsoft for services. In the 2025 calendar year, OpenAI paid Microsoft $10.59 billion for “Research and development” expenses. We believe this most likely refers to the cost of training OpenAI’s models.
Your comment made we wonder what happens when the AI company's new model does not have a dramatic improvement and have just knowledge updates, and majority of the users does not upgrade?
Given the enormous cost of training, would it be worth training new models then?
> Given the enormous cost of training, would it be worth training new models then?
I'm not an expert, but is this even an option? I mean models must be refreshed with latest knowldge base periodically even without algo/design improvements, otherwise the lag become too noticeable and it will hurt users and their use-case.
"Now you see why, when I meet a founder, the first thing I ask about is their growth rate."
This obsession with growth instead of progress or value rubs me the wrong way, given the trend for enshittification of services sooner or later, also remind me of a video I watched yesterday when a founder gives examples of private equity people trying to force growth no matter what:
https://www.youtube.com/watch?v=k4vNIsVY-0Y&t=412s
I thought usually founders try to pivot till they run out of money. I wonder if that is good or bad for a serial entrepreneurs if they decide to shut it down instead of pivoting?
Many founders do try serial pivots until the money's gone. An entrepreneur shutting down cleanly with half the runway still in the bank would be seen by future potential funders as a net positive. It's worse to grind through all the money trying increasingly extreme pivots away from the original.
It takes maturity and decisiveness to recognize when a startup's core idea isn't going to work. In cases where any pivot wide enough to get into different lane is essentially a whole other business, it's often better to just shut down. Even if the last desperate pivot starts to work, you often have some team members and investors who aren't a good fit for the new focus and, worse, the 'new' business that's finally starting to work is almost out of money and the cap table is messed up. It's usually better to shut it down and reboot cleanly.
Founders who've successfully raised millions and executed well are usually quite fundable, even if their first startup didn't work out. Sometimes the timing is wrong or the market evolves differently. The key is how well you think, execute and communicate through both the windup and the wind down.
I feel like pivoting got unwarranted hype in the 2010s or so, possibly because Slack was an outlier in how successful they were.
Major pivoting is almost always a really bad idea. (I admit I'm doing a bit of weaseling using the "major" qualifier, but when I searched for examples online, a lot of the ones that came back weren't major pivots, just slight refinements of focus to find better product market fit). Pivoting usually carries a lot of baggage - better to just give the money back and start afresh most of the time.
He might not have had that choice. Investors can put money into a bank account, and just as easily take it out. This is what happened in the 2000 dotbomb.
I was also wondering if it will result in Helium shortage and even higher prices the next few years, then/if it will be all over, new fabs might also come online and it will be the opposite - a glut. I believe that follows the historic pattern of boom and bust cycles of chip production.
To put this into perspective, India has built 4000+ miles of new railway lines over the last five years including a Shinkansen style bullet train. That’s more than all the railway lines in the country of Switzerland for about $12 billion. The money being thrown around here is mind blowing.
Indeed! And the returns from such an investment in infrastructure will likely be profound.
I feel AI is a bit different, as in there is a spectrum ranging from “utterly stupid” (early ChatGPT), “very helpful” (kinda now), “SkyNet 2.0” (what good are humans!).
As algorithms and technology improve, AI will be both cheaper and more capable. Companies like Anthrophic wouldn’t be the vaulted celebrities as they are today. At that point, I’m not sure what value much of society can provide…
At one time, blacksmiths had a valued place in general society. Today, not so much…
NGL, I would gladly trade opus 4.8 in exchange for my city fixing the roads. Just imagine if even a quarter of the money being dumped into AI went to something that actually improved peoples lives. Man that would be a sight to behold.
Well, if everyone is out of a job, the government is going to have to do something so I’m not too worried about it. If I had to be an optimist about it, I would say that this might be the perfect catalyst to build out a lot of renewable energy (for data centers) and maybe actually implement UBI.
What type of projects you work on, in particular how rich it is in novelty, non-googlable data points and non-trivial project-specific deviations from industry standards?
reply