Ask HN: If the models are so good, why doesn't OpenAI just start 100 companies?
Title is a bit of an exaggeration but the question is more: if the frontier models are so good, why even sell them as your primary money maker?
Couldn't OpenAI or Anthropic make a lot more money by just starting companies themselves that leverage the models and building their own products?
Is selling tokens really the best strategy?
Especially with commodification and prices declining wouldn't that indicate there is more money to be made on the application-side of the models rather than the utility side
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[ 0.21 ms ] story [ 134 ms ] thread2. Selling tokens via long running agents is the only thing that's provably working with respect to revenue growth.
3. They need revenue yesterday. Increases in borrowing rates means access to capital isn't what it was in the 10s. Their runway is much shorter than you would imagine.
4. Some of the decision makers at these companies believe AI will exhibit Jevons Paradox and that any decrease in price will result in induced demand.
5. The frontier models are still subject to the limitations of AI. They're not good at everything. Better to have someone else learn that on their dime rather than yours.
Causality is uncertain, but the "Jevons paradox" interpretation is certainly not contradicted by the available data. Anecdotes of per-employee AI spend rising, and multi-agent freerunning AI tasks becoming more common are also plentiful.
Personally, I think that the "Jevons paradox" interpretation is basically correct. Humanity doesn't have a limited demand on intelligence - but humans are expensive, so it's supply-constrained. The cheaper intelligence gets, the more of it ends up used. As AI gets cheaper and more capable of substituting for human intelligence, usage will rise.
One issue is that token usage and revenue seem to be decoupling in real time. For Jevons paradox to be true, prices need to be going down but total spend on AI has to be going up. That's technically true right now but total usage is going way up while total spend is going up slightly. Another problem is that we may be witnessing the end of "tokenmaxxing" with Anthropic's revenue growth decelerating and OpenRouter's token volume plateauing. Two points of data do not make evidence but the possibility that AI usage is an S curve rather than exponential is live.
Where's the plateau: https://openrouter.ai/data/newsletter/the-token-state-of-pla...
This is a huge problem, why is it like this
In part it is like this because they've already borrowed so much.
Investment isn't debt.
That's what is driving up the cost of debt and teetering some of these companies into junk status.
No they don't.
A company has legal obligation to pay loans at the agreed rates.
There is legal obligation that defines rates of return beyond "acting in shareholder interest" (and OpenAI is a public benefit corporation so even this is reduced).
There just isn’t a sane way to look at this as “investment”
Because it's an investment it is risk capital. They won't be happy if they don't get a return but their return is part ownership in the company, not a legal contract giving an income stream.
Investment isn't debt.
...yet.
One of the biggest AI investors.
Does SoftBank have some absolute blunders on large bets? Totally. Do they make some super weird billion dollar bets? Absolutely. Can you scrutinize them for making some terribly and laughably large bets go to complete zero returns? Sure. But this would be like saying Michael Jordan had a "bad track record" for scoring points because he had games playing for the Wizards where he had like 5 or 10 pts in a game.
When you can throw billions around for investments then on balance you will make a lot of money because you can take a lot of risk. But it does not say anything about any particular investment and if you look at the ratio of good bets to bad bets then SoftBank is terrible. That does not mean they won't make money or that they won't be able to keep doing this. Capital - especially at this level - begets more capital.
How does this explain a $20M bet on Alibaba that netted $60B?
> if you look at the ratio of good bets to bad bets then SoftBank is terrible.
So does a16z, Sequioa, etc...
This is venture investing 101 - they have power law returns. Don't let your survivorship bias cloud your vision.
It's a 26-year-old investment. The advisors who suggested it are long gone from Softbank, and the stake in Alibaba was sold to provide liquidity for bagholder investments like WeWork.
Softbank was lucky, and now their luck is gone. Son had an investment in Nvidia that would have been worth $100+ billion, but sold it in 2019 for only $3.6 billion. Uber is struggling, Arm is a laughingstock of a business, their stake in OpenAI is comically overleveraged, and Softbank Vision Fund is one of the most heavily ridiculed and mocked international VC funds anywhere in the world.
You mean Masayoshi Son, the founder and CEO of SoftBank? lol wut.
https://economictimes.indiatimes.com/news/international/us/s...
> Softbank Vision Fund is one of the most heavily ridiculed and mocked international VC funds anywhere in the world.
Y'all need to stop reading TechCrunch headlines.
Presumably there are penalties if OpenAI were to cancel that order (I am confident that Oracle's army of lawyers made sure to include that). That's the unmovable rock on OpenAI's books, not the data center.
Not a useful term, here.
AIUI, the building is funded by making the people who order it part owners in the new data center company. Not sure and I don’t care enough to find out; clarification welcome.
AnthropenAI are the ones driving a lot of that infrastructure spending when they’re such big consumers of compute but they’re not the ones feeling the brunt of the infra spending. Although those costs will bubble up to them indirectly eventually.
So in effect the debt is backed by OpenAI/Ant's future revenue stream.
Openai haven't yet amortised their current investments into the space and nor have they stopped making new ones.
I'm sure they'd be totally capable of bringing 1k new biz online but that's even more debt, and even more uncertainty.
That all said, A person trusting the big AI companies with their golden goos idea seed leaves a lot of concerning openings down the road if that idea gets "leaked" out to others. Similar concern of mine with if the LLM outputs that made your idea happen to be reused by the big company if someone else asks similar enough questions or otherwise coaxes the AI to reveal what it did for you.
All this AI generation is gonna be a lead to a wild time for IP law.
If they don't make it, there will be plenty of time to mine through their dataset for business ideas to sell to other people as they liquidate. Think of the Spirit Airlines dataset that was just sold.
... and then Salesforce hits them with any number of patent claims. https://insights.greyb.com/salesforce-patents/
One could argue if software patents are good or bad... they're still a fact of "those patents exist and protect functionality." If you're trying to copy the functionality feature for feature, you're likely to step on one.
... and then Salesforce layers get to find out how deep your pockets go for willful infringement.
The counter-argument is that the models might make business ideas just as fungible as anything else.
I've experienced the same thing in real life a couple of times over.
I think Einstein's quote "A new type of thinking is essential if mankind is to survive and move toward higher levels." is apt. Apps will solve a bunch of problems, but if anyone can create those apps, there will be no market for them. I don't have the answers, but long term, it probably doesn't lie in selling apps. We've only just started.
At my regular job, we're just catching up on all the internal work we had. I think there is a real crunch in trying to figure out how to build moats and things that are hard to replicate that are sellable.
Maybe it will be the physical. Probably most of the moat will be made up of network effects and capital intensive processes. If I had the answer I'd probably be working on it right now.
That was somewhat true when execution was time-consuming and expensive.
But original ideas are very far from worthless. They're very rare, because understanding domains and relationships at a deep level is a rare skill.
Meanwhile AI makes execution much cheaper and easier than it used to be.
It seems like the more parsimonious explanation.
Didnt OpenAI build a browser not just AI inside a browser?
https://apps.apple.com/us/iphone/charts/36
That actually makes me wonder if Apple apps are not included because they come pre-installed.
If labor is not your constraint, you wouldn't be diverting your specialization.
Not everything, but a company can be specialized in a lot of different things, Samsung for example, or megacorp in Japan.
The real reason is the models just aren't good enough.
Running a single successful fully automated business at scale would be a huge milestone and a legendary PR achievement, but the tech just isn't there yet.
A machine with infinite attention and infinite knowledge probably could specialize in everything.
They're doing the other thing too via numerous startup acquisitions.
Why go into the hamburger business when you think you've got an infinite profitability recipe on your hand potentially. The big AI houses have doubled down and quadrupled down on their core founding myth for better or worse.
The AI boom is a full send. Either this works in spectacular fashion or it blows in spectacular fashion.
Down the chain you see what you need to do because you work directly with it everyday.
Neither would be easy for either to do
https://www.yahoo.com/entertainment/tv/articles/televised-ne...
I think OpenAI actually will ultimately start a fleet of consultancy/SaaS spinoff companies, each perhaps short-lived until the core product does the job out of the box.
As for the cut, I am sure they will try. Where I work we have had a few projects that were built entirely with models - not a single line written or read by humans. One of them is now the fastest growing money maker for my company, reaching 89M of revenue on about 9% margin in 2 months of its existence, and growing.
It cost roughly 40k in tokens to build, 7 weeks from the first prompt to first production revenue, and was built and is being operated by 1.5 guys. Its a fantastic bang for buck for us, as previously such complex automations would have been impossible to build economically.
There will be an attempt to get a deeper cut of that value. We already see this, for instance, in Meta charging by message on Whatsapp from Oct 1, raising the costs for AI-powered chatbots delivered to consumers via whatsapp by 10-15x easily. More to come for sure.
If you really did it with 1.5 people and it is that profitable, you will have 1000 clones in 1 year. The only moats will be first mover advantage (slim), connections (all right) and the possible secrecy of how much you're making (very slim).