
Why machine learning hyped if easily fooled? - yters
I asked a similar question regarding deep learning, and one answer stated this problem is not unique to DL, but is common to many ML approaches.<p>https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=14850096<p>Given the widespread adoption of ML, shouldn&#x27;t this be of great concern?  Yet I do not see much discussion of ML&#x27;s shortcomings and being easy to manipulate.  Seems an easy to exploit attack vector, could be the next buffer overflow equivalent.
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smt88
1\. Hype is often about how something _will_ be, not how it is today. Examples
include self-driving cars, VR, and even the original iPhone (which didn't have
third-party apps when it was released).

2\. For some uses of ML/DL, it doesn't matter if it's easily fooled. There
will either not be an opportunity to feed it tricky data, or it just isn't a
problem if it makes some mistakes.

