Comment by coffeecoders
6 days ago
Despite the popular take that LLMs have no moat and are burning cash, I find OpenAI's situation really promising.
Just yesterday, they reported an annualized revenue run rate of 10B. Their last funding round in March valued them at 300B. Despite losing 5B last year, they are growing really fast - 30x revenue with over 500M active users.
It reminds me a lot of Uber in its earlier years—fast growth, heavy investment, but edging closer to profitability.
The problem is your costs also scale with revenue. Ideally you want to have control costs as you scale (the first you build is expensive, but as you make more your costs come down).
For OpenAI, the more people use the product, the same you spend on compute unless they can supplement it with another ways of generating revenue.
I dont unfortunately think OpenAI will be able to hit sustained profitability (see Netflix for another example)
"... as you make more your costs come down"
I'd say dropping the price of o3 by 80% due to "engineers optimizing inferencing" is a strong sign that they're doing exactly that.
You trust their PR statements?
8 replies →
> "engineers optimizing inferencing"
They finally implemented DeepSeek open source methods for fast inference?
>(see Netflix for another example)
Netflix has been profitable for over a decade though? They reported $8.7 billion in profit in 2024.
They increased prices and are not selling a pure commodity tho
The bulk of AI costs are NOT in inference. They're in R&D and frontier training runs.
The more inference customers OpenAI has, the easier it is for them to reach profitability.
All costs are not equal. There is a classic pattern of dogfights for winner-take-most product categories where the long term winner does the best job of acquiring customers at the expense of things like "engineering to reduce costs". I have no idea how the AI space is going to shake out, but if I had to pick between OpenAI's mindshare in the broadest possible cohort of users vs. best/most efficient model, I'd pick the customers.
Obviously, lots of nerds on HN have preferences for Gemini and Claude, and having used all three I completely get why that is. But we should remember we're not representative of the whole addressable market. There were probably nerds on like ancient dial-up bulletin boards explaining why Betamax was going to win, too.
We don't even know yet if the model is the product though, and if OpenAI is the company that will make the AI product/model, (chat that keeps expanding into other functionalities and capabilities) or will it be 10,000 companies using the OpenAI models. (well, it's probably both, but in what proportion of revenue)
1 reply →
Unlike Uber or whatsapp, there's no network effect. Don't think this is a winner takes all market, there was an article where we had this discussion earlier. Players who get a small market share are immediately profitable proportional to the market share (given a minimum size is exceeded.)
[flagged]
Anyone concerned about cost should remember that those costs are dropping exponenentially.
Similarly, nearly all AI products but especially OpenAI are heavily _under_ monetized. OpenAI is an excellent personal shopper - the ad revenue that could be generated from that rivals Facebook or Google.
It wouldn't surprise me if they try, but ironically if GPT is a good personal shopper, it might make it harder to monetize with ads because people will trust the bot's organic responses more than the ads.
You could override its suggestions with paid ones, or nerf the bot's shopping abilities so it doesn't overshadow the sponsors, but that will destroy trust in the product in a very competitive industry.
You could put user-targeted ads on the site not necessarily related to the current query, like ads you would see on Facebook, but if the bot is really such a good personal shopper, people are literally at a ChatGPT prompt when they see the ads and will use it to comparison shop.
1 reply →
You raise a good point that this isn't a low marginal cost business like software, telecom, or (most of) the web. Efficiency will be a big advantage for companies that can achieve it, in part because it will let them scale to new AI use cases.
With the race to get new models out the door, I doubt any of these companies have done much to optimize cost so far. Google is a partial exception – they began developing the TPU ten years ago and the rest of their infrastructure has been optimized over the years to serve computationally expensive products (search, gmail, youtube, etc.).
> sustained profitability (see Netflix for another example)
What? Netflix is incredibly profitable.
Probably a bad example from my part, but also because of increasing the costs and offering a tier with ads. I was mostly talking about the Netflix as it was originally concieved. "Give access to unlimited content at a flat fee", which didnt scale pretty well.
1 reply →
As an anecdote they have first mover advantage on me. I pay monthly but mostly because it’s good enough and I can’t be bothered to try a bunch out and switch. But if the dust settles and prices drop i would be motivated to switch. How much that matters maybe depends if their revenue comes from app users or API plans. And first mover only works once. Now they maybe coasting on name recognition, but otherwise new users maybe load balanced among all the options.
I mean sure, it's very promising if OpenAI's future is your only metric. It gets notably darker if you look at the broader picture of ChatGPT (and company)'s impact on our society.
* We have people uploading tons of zero-effort slop pieces to all manner of online storefronts, and making people less likely to buy overall because they assume everything is AI now
* We have an uncomfortable community of, to be blunt, actual cultists emerging around ChatGPT, doing all kinds of shit from annoying their friends and family all the way up to divorcing their spouses
* Education is struggling in all kinds of ways due to students using (and abusing) the tech, with already strained administrations struggling to figure out how to navigate it
Like yeah if your only metric is OpenAI's particular line going up, it's looking alright. And much like Uber, it's success seems to be corrosive to the society in which it operates. Is this supposed to be good news?
I absolutely agree. I find it abhorrent.
Dying for a reference on the cult stuff, a quick search didn’t provide anything interesting.
Scroll through the ChatGPT subreddit right now and tell me there isn't a TON of people in there who are legitimately unwell. Reads like the back page notes of a dystopian novel.
1 reply →
In addition to what the parent commenter was likely referring to, there are also the Zizians: https://en.wikipedia.org/wiki/Zizians
https://futurism.com/chatgpt-mental-health-crises, which references the more famous https://www.rollingstone.com/culture/culture-features/ai-spi... but is a newer article.
4 replies →
Yes but in a typical western business sense they are merely optimizing for user engadgement and profits. What happens to society a decade from now because of all the slop being produced, that is not their concern. Facebook is just about connecting friends right, totally wont become a series of information moats and bubbles controlled by the algorithms...
A great communicator on the risks of AI being to heavily intergrated into society is Zak Stein. As someone who works in education, they are see first hand how people are becoming dependent on this stuff rather than any kind of self improvement. The people who are just handing over all their thinking to the machine. It is very bizarre and I am seeing it in my personal experience a lot more over the last few months.
their moat is leaky because llm prices will be dropping forever and the only viable model will be a free model. Eventually everyone will catch up.
Plus there is the thing that "thinking models" can't really solve complex tasks / aren't really as good as they are believed to be .
I would wager most of their revenue is from the subscriptions - both consumer and business. That pricing is detached from the API pricing. The heavy emphasis on applications more recently is because they realize this as well.
The moat is increasingly becoming having access to billions needed to finance the infrastructure needed to serve billions. That's why Google is still in the game. They have that and they are very good at massive scale and have some cost advantages there.
OpenAI is very good at this as well because of their brand name. For many people ChatGPT is all they know. That's the one that's in the news. That's the one everybody keeps talking about. They have many millions of paying users at this point.
This is a non trivial moat. If you can only be successful by not serving most of the market for cost reasons, then you can't be successful. It's how Google has been able to guard its search empire for a quarter century. It's easy to match what they do algorithmically. But then growing from a niche search engine that has maybe a few tens of thousands of users (e.g. Kagi) to Google scale serving essentially most of this planet (minus some fire walled countries like Russia and China), is a bit of a journey.
So Google rolling out search integration is a big deal. It means they are readying themselves for that scale and will have billions of users exposed to this soon.
> Their last funding round in March valued them at 300B. Despite losing 5B last year, they are growing really fast
Yes, they are valued based on world+dog needing agentic AIs and subscribing to the extent of tens or hundreds of dollars/month. It's going to outstrip revenue things like MS Office in its prime.
5B loss is peanuts compared to that. If they weren't burning that, their ambition level would be too low.
Uber now has a substantial portion of the month. They have about 3-4 billion revenue per month. A lot of cost obviously. But they managed 10B profit last year. And they are not done growing yet. They were overvalued at some point and then they crashed, but they are still there and it's a pretty healthy business at this point and that reflects in their stock price. It's basically valued higher now than at the time of the Softbank investment pre-IPO. Of course a lot of stuff needed to be sorted out for that to happen.
I don't think the no moat approach makes sense. In a world where more an more content and interaction is done with and via LLMs, the data of your users chatting with your LLM is a super valuable dataset.