OpenAI has #5 traffic levels globally. Their product-market fit is undeniable. The question is monetization.
Their cost to serve each request is roughly 3 orders of magnitude higher than conventional web sites.
While it is clear people see value in the product, we only know they see value at today’s subsidized prices. It is possible that inference prices will continue their rapid decline. Or it is possible that OAI will need to raise prices and consumers will be willing to pay more for the value.
Yes, but that is the standard methodology for startups in their boost phase. Burn vast piles of cash to acquire users, then find out at the end if a profitable business can be made of it.
Scams are our entire economy now. Do whatever you can to own a market, then squeeze your customers miserably once you have their loyalty. Cash out, kick the smoking remains of the company to the curb, use your payout to buy into another company, and repeat.
Most startups have big upfront capital costs and big customer acquisition costs, but small or zero marginal costs and COGS, and eventually the capital costs can slow down. That's why spending big and burning money to get a big customer base is the standard startup methodology. But OpenAI doesn't have tiny COGS: inference is expensive as fuck. And they can't stop capex spending on training because they'll be immediately lapped by the other frontier labs.
The reason people are so skeptical is that OpenAI is applying the standard startup justification for big spending to a business model where it doesn't seem to apply.
> Even at $200 a month for ChatGPT Pro, the service is struggling to turn a profit, OpenAI CEO Sam Altman lamented on the platform formerly known as Twitter Sunday. "Insane thing: We are currently losing money on OpenAI Pro subscriptions!" he wrote in a post. The problem? Well according to @Sama, "people use it much more than we expected."
So just raise the price or decrease the cost per token internally.
Altman also said 4 months ago:
Most of what we're building out at this point is the inference [...] We're profitable on inference. If we didn't pay for training, we'd be a very profitable company.
Only in as much as their product is a pure commodity like oil. Like yes it’s trivial to get customers if you sell gas for half the price, but I don’t think LLMs are that simple right now. ChatGPT has a particular voice that is different from Gemini and Grok.
it's a simple problem really. what is actually scarce?
a spot on the iOS home screen? yes.
infrastructure to serve LLM requests? no.
good LLM answers? no.
the economist can't tell the difference between scarcity and real scarcity.
it is extremely rare to buy a spot on the iOS home screen, and the price for that is only going up - think of the trend of values of tiktok, whatsapp and instagram. that's actually scarce.
that is what openai "owns." you're right, #5 app. you look at someone's home screen, and the things on it are owned by 8 companies, 7 of which are the 7 biggest public companies in the world, and the 8th is openai.
whereas infrastructure does in fact get cheaper. so does energy. they make numerous mistakes - you can't forecast retail prices Azure is "charging" openai for inference. but also, NVIDIA participates in a cartel. GPUs aren't actually scarce, you don't actually need the highest process nodes at TSMC, etc. etc. the law can break up cartels, and people can steal semiconductor process knowledge.
but nobody can just go and "create" more spots on the iOS home screen. do you see?
depends if they can monetize that spot. So either ads or subscription. It is as yet unclear whether ads/subscription can generate sufficient revenue to cover costs and return a profit. Perhaps 'enough ads' will be too much for users to bear, perhaps 'enough subscription' will be too much for users to afford.
right now google pays apple almost $30b a year to be default search in safari. google only has one icon on the home screen (YouTube). just originating google searches could be worth tens of billions. so i don't know. there are a bajillion ways to monetize.
I suspect that this orbital data centers isn't entirely about dollars (No doubt dollars are important).
I suspect it is about the regulatory environment. The regulatory environment on data centers is moving quickly. Data centers used to be considered a small portion of the economy and thus benign and not worth extorting/controlling. This seems to be changing, rapidly.
Given that data centers only exchange information with their consumers they are a natural candidate for using orbit as a way to escape regulators.
Further, people are likely betting that regulators will take considerable time to adjust since space is multinational.
True, but businesses don't care about regulations except where it costs them money. Also, remember that time is money, so any regulatory delays cost real money to a business.
My point is that you can actually reduce it all to dollars. And I believe that the cost of orbital data centers will come down due to technological advances, while the cost of regulation will only go up, because of local and global opposition.
"My point is that you can actually reduce it all to dollars."
I'm not sure. A couple of points:
1) The regulatory landscape is enormous. It is unknown from which angle regulators will "slow you down."
2) As I mentioned the regulatory frameworks in this area are evolving very quickly. It is unknown what the regulations will be in 1, 2, 5 years and how that will impact your business.
I think it is also about security. It is impossible for ordinary people to break into such a data center.
It’s a bit like the cyberpunk future when the ultra riches live in moon bases or undersea bases and ordinary people fight for resources in a ruined earth.
Well the argument some of these companies are making is that it would be cheaper over 10 years (some things like power can be cheaper in space, and you can get it from solar nearly 24h a day). It seems likely to me (as it does many other people) that it won't be cheaper, but if it's the same price or mildly more expensive there might be a regulatory incentive to train a ML model in space instead of a place like the EU
IMHO, I doubt they were holding much back. Obviously, they're always working on 'next improvements' and rolled what was done enough into this but I suspect the real difference here is throwing significantly more compute (hence investor capital) at improving the quality - right now. How much? While the cost is currently staying the same for most users, the API costs seem to be ~40% higher.
The impetus was the serious threat Gemini 3 poses. Perception about ChatGPT was starting to shift, people were speculating that maybe OAI is more vulnerable than assumed. This caused Altman to call an all-hands "Code Red" two weeks ago, triggering a significant redeployment of priorities, resources and people. I think this launch is the first 'stop the perceptual bleeding' result of the Code Red. Given the timing, I think this is mostly akin to overclocking a CPU or running an F1 race car engine too hot to quickly improve performance - at the cost of being unsustainable and unprofitable. To placate serious investor concerns, OAI has recently been trying to gradually work toward making current customers profitable (or at least less unprofitable). I think we just saw the effort to reduce the insane burn rate go out the window.
1) LLM advances stop
2) The Chinese companies release open source/weight models which are as good or better than the West
3) Apple somehow turns it around with AI
Apple is done for.
AI is going to be central to the next generation of phones and the next form factor.
Their complete failure on AI has been ... shocking. Not sure if they don't have the data to train a leading edge model or if they have some kind of personele issue, it has just been shocking to see their lack of progress.
No doubt Apple has rested on their laurels for a long time. I just would not have expected this.
It looks like she buys and holds, unlikely nancy. And it looks like she bought some AMD which had great returns (oh how I wish I bought it) and held it.
He will be missed.
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