[visarga]

Bullshit. Write me a better cat detector in SQL, or protein folder, or super-human board game player. And, by the way, ML does write SQL [1].

Deep learning has all these disadvantages and difficulties because we moved the goalposts too many times and now want so much more out of it than regular software. A model has to be accurate, but also unbiased, updated timely and explainable and verified in much detail; also efficient in terms of energy, data, memory, time and reuse in other related tasks (fine-tuning).

We already want from an AI what even an average human can't do, especially the bias part - all humans are biased, but models must be better. And recently models have been made responsible with fixing societal issues as well so they've become a political battleground for various factions with different values - see recent SJW scandals at Google.

With such expectations it's easy to pile on ML but ML is just a tool under active development, with practical limitations, while human problems and expectations are unbounded.

[1] a neural SQL patent: https://patentimages.storage.googleapis.com/af/78/be/92ee342...