> Modern GPUs are expensive, so it seems difficult to build a homelab to play around with them. Simulate a system with multiple high-end GPUs by setting up a s

> Modern GPUs are expensive, so it seems difficult to build a homelab to play around with them. Simulate a system with multiple high-end GPUs by setting up a system with one low-end GPU, breaking all the video outputs, and plugging it into a timeswitch that makes it lose power 3 times a week. Learn about industry norms by deciding it's crucial you have read access to production data, but at the same time that your users are doing ad-hoc experimentation and they can barely meet the code maturity requirements of a test environment. Fill your storage with training data for a project, then have that project "de-prioritised" so the data isn't being used, but it also can't be deleted. Reorganise the department so it's not even clear whose data it is any more. Broaden your experience to the entire mlops lifecycle by memorising the crucial shibboleth: "I don't understand labelbox's pricing"