People use image generation AI every day now, but I feel like almost nobody actually understands what training one looks like underneath. Every time I search about it, I either find insanely complex research papers or fake “train your own AI in one click” videos that skip everything important.
It genuinely makes me curious what the real workflow looks like behind training even a small image generation model from scratch just as an experiment. Like how hard is it actually? What part is the real bottleneck? The compute, the data, the architecture, or just understanding all the moving parts together?
AI image generation already feels normal now, but the process behind creating those systems still feels weirdly hidden from most people.
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