You should probably disclose that you're a CTO at an AI startup, I had to click your bio to see that.

> The amount of compute in the world is doubling over 2 years because of the ongoing investment in AI (!!)

All going into the hands of a small group of people that will soon need to pay the piper.

That said, VC backed tech companies almost universally pull the rug once the money stops coming in. And historically those didn't have the trillions of dollars in future obligations that the current compute hardware oligopoly has. I can't see any universe where they don't start charging more, especially now that they've begun to make computers unaffordable for normal people.

And even past the bottom dollar cost, AI provides so many fun, new, unique ways for them to rug pull users. Maybe they start forcing users to smaller/quantized models. Maybe they start giving even the paying users ads. Maybe they start inserting propaganda/ads directly into the training data to make it more subtle. Maybe they just switch out models randomly or based on instantaneous hardware demand, giving users something even more unstable than LLMs already are. Maybe they'll charge based on semantic context (I see you're asking for help with your 2015 Ford Focus. Please subscribe to our 'Mechanic+' plan for $5/month or $25 for 24 hours). Maybe they charge more for API access. Maybe they'll charge to not train on your interactions.

I'll pass, thanks.

Datacenters full of GPU hosts aren't like dark fiber - they require massive ongoing expense, so the unit economics have to work really well. It is entirely possible that some overbuilt capacity will be left idle until it is obsolete.

> Inference providers are already profitable.

That surprises me, do you remember where you learned that?

> The amount of compute in the world is doubling over 2 years because of the ongoing investment in AI (!!)

which is funded by the dumping

when the bubble pops: these DCs are turned off and left to rot, and your capacity drops by a factor of 8192