the nature of the test was to see if the models can effectively compose an image of a novel concept outside the training set. If they are trained on it, it ceases to be an interesting test to some extent.
I would urge you to re-read the blog post you are commenting on. It pretty clearly explains how it is an interesting test independently of "see[ing] if the models can effectively compose an image of a novel concept outside the training set".
it's still interesting because there's no pelican-on-bike model, and if you're training a model well enough, then it should be obvious when a model has reached "AGI" or whatever.
Would it? Tongue in cheek.
and that is bad because ?
the nature of the test was to see if the models can effectively compose an image of a novel concept outside the training set. If they are trained on it, it ceases to be an interesting test to some extent.
I would urge you to re-read the blog post you are commenting on. It pretty clearly explains how it is an interesting test independently of "see[ing] if the models can effectively compose an image of a novel concept outside the training set".
it's still interesting because there's no pelican-on-bike model, and if you're training a model well enough, then it should be obvious when a model has reached "AGI" or whatever.