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A good fix would, in my opinion, understanding how the algorithm is actually categorizing and why it miss-recognized gorillas and humans.

If the algorithm doesn't work well they have problems to solve.

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But this is not an algorithm. It's a trained neural network which is practically a black box. The best they can do is train it on different data sets, but that's impractical.

That's exactly the problem I was trying to reference. The algorithms and data models are black boxes - we don't know wat they learned or why they learned it. That setup can't be intentionally fixed, and more importantly we wouldn't know if it was fixed because we can only validate input/output pairs.

It's too costly to potentially make that mistake again. So the solution guarantees it will never happen again.

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