LLMs on device is the future. It's more secure and solves the problem of too much demand for inference compared to data center supply, it also would use less electricity. It's just a matter of getting the performance good enough. Most users don't need frontier model performance.
I see a lot of people are confused about the electricity claim so I'll elaborate on it more. The assumption I'm making here is that on device people will run smaller models, that can fit on their machines without needing to buy new computers. If everyone ran inference on their machine there would be no need for these massive datacenters which use huge quantities of electricity. It would utilize the machines they already have and the electricity they're already using.
People are making a comparison of the cost per inference or token or whatever and saying datacenters are more efficient which makes obvious sense. What i'm saying is if we eliminate the need for building out dozens of gigawatt datacenters completely then we would use less electricity. I feel like this makes intuitive sense. People are getting lost in the details about cost per inference, and performance on different models.