> during the first year of grad school I realized that AI, as practiced at the time, was a hoax. I had a similar realization during grad school about a lot of the popular topics at the time (early 2000s). I even used to call them "the hoaxes of computer science". Things like grid computing or formal methods of software engineering had a lot of resources behind them, but nobody was able to use the results. Instead, ve…
Funny because I do have the same feeling these days: that ML is a hoax. Even funnier: I do have a master's degree in ML.
It doesn't even make sense, it's like saying marijuana is a hoax because my uncle smokes pot and still got cancer.
Here are some alternative statements that make more sense (and contain more truth):
* There is a lot of snake oil and outright fraud being sold to unwitting managers.
* There is a lot of empty hype being fed to general public through the pop sci media and mainstream news.
* Deep learning specifically has not borne fruit in all (edit: or even most) problem domains.
* Lack of good quality data (and qualified people to analyze it) is a bigger problem than lack of advanced models and computing power.