"Stephen Grossberg explains why his ART model is better" Please don't explain me why your model is better. _show me_ your model is better with results. I see

"Stephen Grossberg explains why his ART model is better" Please don't explain me why your model is better. _show me_ your model is better with results. I see a lot of: "this model is explainable and has no forgetting modes". But I cannot care about an explainable model that does not work. There are many classic explainable models, how do they compare to art in real life applications? "The problem with today’s AI, he says, is that it tries to imitate the results of brain processing instead of probing the mechanisms that give rise to the results." Today's AI works really well for many applications (computer vision has leaped in quality). But of course I did not expect perfection from ImageNet trained models. I also did not expect gpt3 to be agi. But are they good (especially when compared with what we had not long ago)? Hell yeah Also, the advancements in protein folding are superb. I understand the author is not dismissing the current advancement. But if you claim your model is better you ought to compare it with the state of the art