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pitchedyesterday at 5:49 PM2 repliesview on HN

For a business with ten or more engineers/people-using-ai, it might still make sense to set this up. For an individual though, I can’t imagine you’d make it through to positive ROI before the hardware ages out.


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zozbot234yesterday at 6:01 PM

It's hard to tell for sure because the local inference engines/frameworks we have today are not really that capable. We have barely started exploring the implications of SSD offload, saving KV-caches to storage for reuse, setting up distributed inference in multi-GPU setups or over the network, making use of specialty hardware such as NPUs etc. All of these can reuse fairly ordinary, run-of-the-mill hardware.

DeathArrowyesterday at 6:42 PM

Since you need at least a few of H100 class hardware, I guess you need at least few tens of coders to justify the costs.

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