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There is also a push to run machine learning models on low-resource devices, which a $4 VPS could be categorized as.

https://www.tensorflow.org/lite

https://huggingface.co/muhtasham/olm-bert-tiny-december-2022

https://neuml.hashnode.dev/train-a-language-model-from-scrat...

I remember some CPU-overloading loads categorized as "mining" in various cloud providers and shut down. I wonder if ML training will cause the same false-positives. (Or "true positive" in the case of "excessive load not allowed" providers)

This concept was more for inference on-demand vs training a model. For example, if there was an API call that had a model call as part of it's workflow. Training even a small model still requires serious compute power.

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