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@@ -22,7 +22,7 @@ Based on [[https://schlockmercenary.fandom.com/wiki/The_Seventy_Maxims_of_Maxima
*. If you’re not willing to prune your own layers, you’re not willing to deploy.
*. Give a model a labeled dataset, and it trains for a day. Take its labels away and call it “self-supervised,” and it’ll generate new ones for you to validate tomorrow.
*. If you’re manually labeling data, somebody’s done something wrong.
*. Training loss and validation loss should be easier to tell apart.
*. Memory-bound and compute-bound should be easier to tell apart.
*. Any sufficiently advanced algorithm is indistinguishable from a matrix multiplication.
*. If your model’s failure is covered by the SLA, you didn’t test enough edge cases.
*. “Fire-and-forget training” is fine, provided you never actually forget to monitor the run.