Comment by qalmakka
7 hours ago
I never truly understood what the intended business model around LLMs was. Get them widespread through cheap pricing and then jacking it up? Being the only ones that had a viable product so to get the ability to extract as much value as you want from AI?
I don't understand how a product that:
- is interfaced with and is deeply linked to natural language, so everything you produce (sessions, history, etc) is in Markdown and you can literally install a second model and tell it "hey import all of Claude's memory into yours" and that's it
- is based on well understood technology, the real constraints are how much money you put into training the models, but the theory has all been developed in the open
- clearly has a threshold where it quickly commoditises and turns from "I want the best" to "hey the best is a bit too expensive. The second best is half the price and works close enough".
was ever supposed to be a money printing machine. The fact something is extremely useful doesn't imply it's extremely profitable.
IMHO we're clearly speedrunning the process of turning AI into a commodity. Dario Amodei knows pretty well that when or if Anthropic cuts people off Fable, the vast majority of them will definitely not pay for it because Opus 4.8 is good enough for almost everybody that _knows_ what they're doing, and so are basically half of the most recent models. If I already have good baking skills I don't become more productive with an automatic bread machine, I just need a better dough mixer and oven
There is no business model. That’s not a joke, the idea is to be the one that survives the race, then figure out how to be profitable. If you look at the level of capex and money raised, that’s not something you do if you have an actual business plan. We are very far from business fundamentals
> I never truly understood what the intended business model around LLMs was.
A closely related question is “what do the American labs need to do in order to justify their enormous market valuations?”
It seems like the answer cannot possibly be “gradually improve model capability while figuring out how to better monetize inference.” The valuations are just way too high for that to be sufficient.
Surely the answer has to be “continually achieve large leaps in capability comparable to the first consumer releases of ChatGPT while also maintaining a significant capability lead over open models and new competitors.”
And does anyone think that’s going to happen? Even with state-level protection from competition (which incidentally would significantly harm the American economy), the large leaps in capability seem to be coming fewer and farther between.
> I never truly understood what the intended business model around LLMs was
What appeared initially to be a huge innovation was later easily duplicated by many. There are no platform-lockins or network effects. Switching costs for users are zero, and there are low barriers to entry, with vast numbers of models to choose from and more appearing every day. As a business a token will be a commodity like an electron. Doesnt matter who produces it, or how (solar, wind, coal, nuclear etc) as long as it powers my toaster.
It's fairly simple. Sell GPU compute + extra margins as only some GPUs can load the models + extra margins based on how much better closed source models are from open source ones + hopefully reduced cost due to batching
It seems like the endgame is to amass absurd amounts of hardware and produce something that will replace you the baker entirely
everything else we see today is just preparing for it.
Same business model as always: build cool tech because it is cool and figure it out later.
The valuation is based on one lab getting a decisive first advantage, and turning that into a durable self-improving advantage that can never be caught up to. If any can pull it off (a gigantic if), they will effectively own most AI value, and the people who own their shares will live happily ever after. Divide your investment between the labs that could plausibly do this, and your EV may not be dreadful.
This is clearly not how it's going though. Any advancement from any lab has been quickly (< 6 months) matched up by basically everybody else. Even Grok nowadays is decent, and that's something. When something like you've described actually happened historically you generally had quite fast a clear frontrunner and a bunch of copycats that failed miserably; in 2026 we are very far from that. we are heading face-first into towards a pricing war because all models are easily interchangeable nowadays - AI is turning into a commodity more or less
And then you wake up from the dream…