LLM Inevitabilism

If in 2009 you claimed that the dominance of the smartphone was inevitable, it would have been because you were using one and understood its power, not because you were reframing away our free choice for some agenda. In 2025 I don't think you can really be taking advantage of AI to do real work and still see its mass adaptation as evitable. It's coming faster and harder than any tech in history. As scary as that is we can't wish it away.

Ironically, this is exactly the technique for arguing that the blog mentions.

Remember the revolutionary, seemingly inevitable tech that was poised to rewrite how humans thought about transportation? The incredible amounts of hype, the secretive meetings disclosing the device, etc.? That turned out to be the self-balancing scooter known as a Segway?

1. The Segway had very low market penetration but a lot of PR. LLMs and diffusion models have had massive organic growth.

2. Segways were just ahead of their time: portable lithium-ion powered urban personal transportation is getting pretty big now.

Massive, organic, and unprofitable. And as soon as it's no longer free, as soon as the VC funding can no longer sustain it, an enormous fraction of usage and users will all evaporate.

The Segway always had a high barrier to entry. Currently for ChatGPT you don't even need an account, and everyone already has a Google account.

This is wrong because LLMs are cheap enough to run profitably on ads alone (search style or banner ad style) for over 2 years now. And they are getting cheaper over time for the same quality.

It is even cheaper to serve an LLM answer than call a web search API!

Zero chance all the users evaporate unless something much better comes along, or the tech is banned, etc...

> LLMs are cheap enough to run profitably on ads alone

> It is even cheaper to serve an LLM answer than call a web search API

These, uhhhh, these are some rather extraordinary claims. Got some extraordinary evidence to go along with them?

I've operated a top ~20 LLM service for over 2 years, very comfortably profitably with ads. As for the pure costs you can measure the cost of getting an LLM answer from say, OpenAI, and the equivalent search query from Bing/Google/Exa will cost over 10x more...

Profitably covering R&D or profitably using the subsidized models?