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api an hour ago

This is part of why I think the data center build-out is a bubble. We've barely scratched the surface when it comes to hardware optimization. We'll see exponential improvements in energy efficiency and speed over the next decade. Exponential, not linear.

GPUs really aren't that great for AI. They just happen to be the best chips we have in mass production right now for this work load, and it takes time to field new designs. Basically every chip engineer on the planet is working on this right now.

mindwok an hour ago | parent | next [-]

Whether it's a bubble or not depends on how much the demand for compute and the type of workload keeps growing, though.

If AI tends to be something used mainly in ideation and development, which is how a lot of people use it today, then once consumer hardware gets good enough you could see a bunch of the current data centre workloads move onto consumer devices.

But if AI starts being used more in repeatable, operational workloads I think it makes sense to have significant cloud infrastructure for it. TBH I haven't seen much of this, and I've been skeptical about people using agents for much of anything when it can be done with just software. But we are starting to see more of this kind of workload, like the taggable Claude in your slack etc that people seem to really love.

winrid an hour ago | parent | prev [-]

On the plus side, lots of cheap servers to swoop up :)

sroussey 43 minutes ago | parent [-]

But power hungry.

In that 5+ year timeline, the compute per watt could change by three orders of magnitude.

GPUs are to LLMs what CPUs are to gaming — not a good fit.