As of 2020, we have come a long way with respects to applying novel learning algorithms through deep learning to vision tasks — otherwise a characteristic feature of most living beings that move. In “narrow” tasks like object detection and classification, different labs have reported “better than human” level performance of machines. However, multiple bottlenecks have arose in the application of these algorithms to “real world” where humans still have a massive generalizing upper hand. A rather simple research work on corrupting MNIST data, dubbed MNIST-C, highlights this difference quite well. The gist being that distorting/corrupting images of MNIST (handwritten…

Mrinal Sourav

AI/ML Researcher

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