I know a traditional SaaS company I worked for that IPO’d years ago and still has no signs that they can be profitable (and many others like it) and nobody seems particularly concerned.
the market cap of a company is computed by the current price of a company's shares, the last price paid; not all the shares of the company were bought at that price, the ones who got shares cheaper are showing paper profits, unrealized. Those who have already cashed out have money in their bank accounts that was transferred from people who wanted to get in. If the company goes bankrupt, their shares will be worthless, but the money they paid for them still remains in the accounts of people who sold their shares: the money was not lost even if some people lost money.
I'm not going to keep going through it but the reason it works to value things the way we do is that the values are comparable and they frequently work out, so snapshots of the economy and the participants are comparable. But "losses" are not like taking gold and feeding it into some deep fold in the earth where it will disappear into the molten middle of earth.
Stock valuations are "expectations for the future". Those expectations weren't money, they were lottery tickes where the lottery consisted of human creativity and human effort. People buying and selling share are moving real money around to trade the expectations. The money didn't go anywhere, it's still there, it's just that expectations for the future have been reduced. It all boils down to humans trading some of their time and potential on a bet that things work out. Some people's effort gets more rewarded than others. Not every team wins the world cup, but people like to play and like to watch.
If they fail then the negative impact ripples through the economy due to misallocation of resources.
And I think we passed the threshold for crash down for AI, even if AI companies wont be that profitable. Nvidia/cloud providers will be profitable as long as there is demand for AI.
If AI companies aren't that profitable...then they're going to stop spending so much money on GPUs to train AI models. A gigantic amount of Nvidia's profits would go bust overnight.
AI usage seems to have plateaued overall [2], except for niche use cases like coding, that is why companies are forcing it on their employees to justify ROI [3] or creating "products" w/ AI features [4] or embedded addiction.
[1] https://news.ycombinator.com/item?id=48241012
[2] https://news.ycombinator.com/item?id=48179021
https://www.theinformation.com/articles/anthropic-openais-sh...
I sure hope more people think like this, because it's going to leave a lot of money on the table (for me)
And if they are right then what? You won't get a lot of money?
Seems like a weird mix of inflated ego and lack of business understanding by you on this comment.
I don't know what your statement is but if you are an employee, then as your employer is forcing you to tokenmax and forcing you to use slop and creating leaderboards for these token spend which will all end up forcing the company to bleed money afterwards they might even lay off people.
If you are an employer then there are still long term issues associated. For example, cloudflare is a company which hasn't been in profit but it has burnt through 5 million dollars per month for AI as it first created an incentive (shrewd even) for employees to use it (for everything) only to please the investors but in the end, its still unclear how profitable all of it is for cloudflare.
Perhaps I have misunderstood you but I really don't understand how its going to leave a lot of money on the table, the only thing I see is a race to the bottom.
The weird thing is that so many people believe that inference is unprofitable. There are large open weights models that companies run at a profit while charging far less than what OpenAI and Anthropic charge. Deepseek V4 just made their 75% off deal permanent and it was already very cheap.
Yes, you have to consider costs of training the models, but as usage grows it’s going to become a smaller and smaller part of the business.
I think we will see some data center businesses and AI companies blow up, but I think the people expecting the entire AI scene to blow up because prices quadruple are going to be disappointed.
You have no idea whether those companies are making a profit.
1. All it takes is one of them operating a loss to gain market share to force the other ones to lower prices to compete.
2. There’s not reason to expect that these relatively small companies are correctly pricing GPU depreciation.
I doubt the various providers on OpenRouter are benevolently operating at a loss because they’re so generous.
You can also calculate the cost to run these models yourself. They are open weight and the hardware required to run them is not a secret. They can be modeled and many have done the business modeling.
I’m always surprised at how many Hacker News commenters are unaware that a lot of financial modeling and analysis has been done on these companies and models. It’s naive to think the the hottest topic in tech has not already been dissected and analyzed by the finance industry at every level.
Privatize Profits and Socialize Losses is now Bog-Standard Operating Procedure.
The stock market. Stocks crash, companies go belly-up, tons of people get laid off, unemployment spikes, people die. I don’t give a shit about the companies themselves. I do give a shit about who they employ, both directly and downstream, and the job market that will result from many of them losing their jobs.
In 10 years, we've spent nearly 3x the cost of the entire US interstate highway system on AI.
Some helpful visualizations: https://www.aljazeera.com/news/2026/2/19/visualising-ai-spen...
(Is there a more extreme example so far of this than AI companies, just in terms of raw losses? As far as I know, Netscape's lifetime losses as an independent company "only" total a bit over $100 million dollars, which is a lot, it just doesn't look like all that much when put into perspective...)
We can look at a “success story” like Uber and it is still net negative over its entire existence. This is a business that’s in a literal monopoly/duopoly status in most markets it operates in with vastly reduced regulatory burden compared to the industry disrupted. Literally the ideal scenario for printing money and yet it hasn’t made any. It’s the poster child for the unicorn exit that founders dream of.
The end result is that Uber and companies like it are a financial instruments that transfer dollars away from one set of investors to another set of investors.
If Uber hasn’t yet made its investment back, I struggle to wonder how some of these AI ventures will ever make that money back when their expenditures make Uber look like a small little side project.
Meta has spent almost 4 years worth of its net income for FY2025 on AI going by this website’s data, and counting.
We are decades since Web 2.0 took off, almost 20 years since the iPhone launched, 50 years of Apple Computer. Software isn’t some new industry anymore. There isn’t an industry left that hasn’t completed its digital transformation. These spray and pray economies would have died off years ago if it wasn’t for the fact that software companies have uniquely low cost structures where they don’t need to build factories or distribution networks to get their products to their customers. These low cost structures might just be concealing the fact that it’s not going to be a growth industry forever.
How has the sheer saturation of LLMs not resulted in profit? It has dominated the conversation, center stage, of every news outlet for like 4 years now. It is the most known-about thing currently out there.
And we haven't been able to convert that much captured attention into profitability yet? That seems... bad?
Maybe Reddit is an example? But my impression is that they ran a modest operation before going public.
ChatGPT is the 5th most visited website in the world. Gemini.Google.com is ranked above amazon.com. Where is the profit?
