(no title)
obirunda | 22 days ago
Future better models will both demand higher compute use AND higher energy. We cannot underestimate the slowness of energy production growth and also the supplies required for simply hooking things up. Some labs are commissioning their own power plants on site, but this is not a true accelerator for power grid growth limits. You're using the same supply chain to build your own power plant.
If inference cost is not dramatically reduced and models don't start meaningfully helping with innovations that make energy production faster and inference/training demand less power, the only way to control demand is to raise prices. Current inference costs, do not pay for training costs. They can probably continue to do that on funding alone, but once the demand curve hits the power production limits, only one thing can slow demand and that's raising the cost of use.
No comments yet.