I keep reading about how AutoML will make things more efficient, but in my experience it's been hideously expensive in both time and cost (and I am therefore gu

I keep reading about how AutoML will make things more efficient, but in my experience it's been hideously expensive in both time and cost (and I am therefore guessing energy), and had yielded marginal improvements at best. Often I have encountered AutoML in the form of an overfit model with test data leaks that has underperformed in prod having overperformed in test. So - I don't see how AutoML is going to discover more efficient layers without expending loads of energy, can you describe how it will contribute to lowering the whole energy budget? On the models as oss thing - I think everyone likes this idea, but models are not the same as code andoss doesn't always produce good code cf. desktop linux.