Help me out. I am naive about neural networks. I have skimmed the paper, read the abstract and he conclusion and looked at the examples.
Does this not illustrate what is the fatal flaw in image recognition based approaches with neural networks, that their failure modes are inscrutable?
80% or 95% of the time they do well but the corner cases where they do poorly they fail in ways that are entirely unlike the was our brains' systems fail. Unpredictably. So they can be useful for non critical applications but not critical applications. Like self driving cars....
Stages of grief here... I was looking forward to my car with a cocktail cabinet that would drive me to parties and home again... I believed the hype five years ago. Is this why progress has stalled?