I really wish the press (and a subset of highly vocal Deep Learning practitioners) would stop conflating Deep Networks with the entirety of AI/ML. This hallucin

I really wish the press (and a subset of highly vocal Deep Learning practitioners) would stop conflating Deep Networks with the entirety of AI/ML. This hallucination problem is 1) highly pronounced in this one class of methods that has surged in popularity in the last 10 years 2) difficult to address because these methods are (so far) quite opaque to human understanding I work on multiple in-production vision systems and in cases where we absolutely need to know why something went wrong we use much more conventional, but more transparent, learning algorithms. The performance loss is often an acceptable tradeoff for being able to understand your edge cases.