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You are completely wrong and will never make a good product/service with that attitude. You need to test the models work for your use case. Knowing how much of
by danielmarkbruce 2mo ago
You are completely wrong and will never make a good product/service with that attitude. You need to test the models work for your use case.
Knowing how much of type X data a model was trained on isn't going to help you one bit. Various phases of training can effectively wipe out the training from earlier steps if not done well. All that matters is does the model do what you want it to do. In practice almost everything in AI/ML is empirical.
- overgard 2mo agoMate, I have 20+ years of experience writing software, I'm not really worried. Frankly if I never used a model ever again I would still write software just fine. These things are conveniences to me, not load bearing.
- danielmarkbruce 2mo agoYep, if you aren't really using models, then you don't have to evaluate them. If you want to build a product where the model is bearing load, which is probably 90% of new software built over the next 20 years, you'll have to evaluate the model yourself.