You’re just repeating the same point I’ve just addressed, so I’ll explain in more detail.
Data centres expanding is perfectly compatible with huge efficiency gains per token. If the cost of inference falls, companies can afford to run vastly more inference, serve more users, use larger models and embed AI into more products.
It’s the same reason more fuel-efficient cars didn’t eliminate demand for roads or petrol. Efficiency lowers the cost of using something, which can increase total consumption.
So “if software got more efficient, they wouldn’t need more data centres” is basically backwards. The relevant question is whether total AI demand is growing faster than efficiency is improving.
You’re just repeating the same point I’ve just addressed, so I’ll explain in more detail.
Data centres expanding is perfectly compatible with huge efficiency gains per token. If the cost of inference falls, companies can afford to run vastly more inference, serve more users, use larger models and embed AI into more products.
It’s the same reason more fuel-efficient cars didn’t eliminate demand for roads or petrol. Efficiency lowers the cost of using something, which can increase total consumption.
So “if software got more efficient, they wouldn’t need more data centres” is basically backwards. The relevant question is whether total AI demand is growing faster than efficiency is improving.
So your really making the claim that there’s over a 900x demand for AI in the last year?
I’m calling bullshit.
No.
?
When you lock onto something really hard in a discussion like this it becomes very obvious you’re faltering and dont really have much to contribute.
Ypu claimed up above a 900x increase in token efficiency, and claim that demand is outpacing efficiencies.
So yes you are.
I’m calling bullshit on demand outpacing efficiencies in general.