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Wow, love the NNMF visualization. Like all great visualizations, it does a very good job of showing and not telling me what's going on. More of this, please. One question: how does this kind of thing line up with what people describe as "explainable AI?"

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It's not explainable until all these weights are between unambiguous concepts in a knowledge base rather than plain text tokens that must be interpreted. For some reason we gave up on symbolic AI in the 70's and decided making machines write poetry is where the money's at.

These are AI explanation methods. They belong to the toolbox which would include LIME, Shapley values...etc. Input saliency is a gradient-based explanation method.

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