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Comment by clircle

5 years ago

Machine learning is a hammer and there are just not very many nails. However there are a lot of screws that we wish were nails. Or we pretend they are nails.

I came out of college super excited about machine learning because the math was so interesting and there was a sense of boundless utility and applicability. I came to realize that, at least in industry, the utility is mostly ad targeting and other stuff that doesn't really matter, and other than that ML is mostly overpowered for the task. There is not much socially positive application of machine learning, mostly socially neutral or negative. Some positive, sure, like there's some in medicine, but my understanding is the hardness there is not algorithmic.

  • > There is not much socially positive application of machine learning, mostly socially neutral or negative.

    How do you arrive at this conclusion? What about Computer Vision? Speech recognition and synthesis? Fraud detection? Sentiment analysis?

    • I'm not saying every application is bad. It's just that most of the positive applications seem to mostly be data aggregation and cleaning problems, not hard ML problems. Most of the time it's really a simple algorithm with a lot of good data that you need, there's not much interesting work to do besides plugging things together