2026-04-29 01:43 UTC
@anildash I also like that it's designed to solve a particular problem. That makes it easier to evaluate its performance.
And I have the impression from the "Power hungry processing" paper that purpose-built models used less energy for the same task than general purpose models.
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@dhobern@scicomm.xyz 2026-06-03 04:49
@nyhan@fediscience.org @anildash@me.dm Any worthwhile model needs a way that its fit to some criterion of truth can be measured. Many machine learning models are about classifying data or predicting values in ways that can be tested. Then the performance of the model against reality can be defined and documented. With generative AI, there is rarely any objectively measurable criterion to assess the quality of the results other than the vagaries of user taste. This is what has led to so much over-hyping of mediocre result-shaped outputs.