Just picking one company who basically just does AI, OpenAI. They reported it has 20 million PAID subscribers to ChatGPT. With revenue projected above $12b dollars (https://www.theverge.com/openai/640894/chatgpt-has-hit-20-mi...).
I think what you meant to say is that costs are high so they can't generate large profits. but saying that they can't figure out how to sell it seems absurd. Is it Netflix level of subscribers, no. But there can't be more than a couple of hundred products that have that type of subscription reach.
The better question is what if all LLM services stopped providing for free at all -- how many paid users would there then be?
This is very similar to Uber which lost money for 14 years before becoming profitable, but with significantly more upside.
Investors see the growth, user stickiness and potential for the tech; and are throwing money to burn to be part of the winning team, which will turn on the money switch on that userbase down the line.
The biggest companies and investors in the planet aren't all bad at business.
You can if you're still growing. ChatGPT is the 5th most visited site on the planet yes, but it is still growing hundreds of millions of visits with every passing month.
They aren't turning a profit because they aren't monetizing the vast majority of subscribers in any way (not even ads). LLM inference is cheap enough for ads to be viable.
Because 50 gigs is next to nothing, and you only need a rinky dink amount of compute to write files.
YouTube, on the other hand, is actually pretty expensive to operate. Takes a lot of storage to store videos, never mind handling uploads. But then streaming video? Man, the amount of bandwidth required for that makes file syncing look like nothing. I mean, how often does a single customer watch a YouTube video? And then, how often do people download files from Dropbox? It's orders of magnitude in difference.
But LLMs outshine both. They require stupid amounts of compute to run.
The fundamental problem has already been mentioned: Nobody can figure out how to SELL it. Because few people are buying it.
It's useful for aggregation and summarization of large amounts of text, but it's not trustworthy. A good summary decreases noise and amplifies signal. LLMs don't do that. Without the capability to validate the output, it's not really generating output of lasting value. It's just a slightly better search engine.
It feels like, fundamentally, the primary invention here is teaching computers that it's okay to be wrong as long as you're convincing. That's very useful for propaganda or less savory aspects of business, but it's less useful for actual communication.