this post was submitted on 28 May 2026
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Fuck AI
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AI, in this case, refers to LLMs, GPT technology, and anything listed as "AI" meant to increase market valuations.
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Trying to etch models into a chip is a dead end until we reach “peak” quality.
However, unless they include some kind of LoRA (low-rank adaptation) adapter onto the silicon, it severely limits the utility of whatever model or architecture they choose. Being able to modify the weights is way more useful.
Honestly, diffusion decoders are probably where we’ll end up some day. Not end there, but that’s probably the next logical step in the throughput chain.
General purpose compute is infinitely more valuable during times of great software improvements than highly specialized compute.
Things like Tensor Processing Units (TPUs) still aren’t ubiquitous yet, even though they’ve been around for 10+ years. They’re Too specialized to allow for reasonable flexibility on testing.
They claim they can apply Lora's to it, and that at a data centre scale, it will pay for itself in a year vs existing GPU methods... but who knows if any of that is true.
They'd need a pretty good recycle process set up to get rid of cards that are no longer useful after a couple years as well.
But ya, maybe this is future future, once we have these amazing models that don't need to be changing often.
Edit: and some models would be better suited for it than others. A creative writing model is less likely to suffer not being updated as frequently as a programming model for example.