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Given that a lot of computer vision work is based on randomised algorithms, do you think that these standards would be enough? You could demonstrate 100% MC/DC coverage through a neural net implementation, but the weights are where the faults probably exist, for example.


That actually leads to a very interesting point; would self driving cars be vulnerable to adversarial imagery?

Neural nets are well known for being easily fooled [1] ... I wonder if you could create similar situations for self-driving cars.

[1] http://www.evolvingai.org/fooling




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