“ Deep neural nets are machine learning algorithms that learn “rules” from data, while expert…
Louis Savain

I don’t know any detriment, so here is my denial:

  1. The “rules” that come from neural networks are not simply “ IF A THEN B”. There is at least some arithmetic processing, at least a linear combination of input values. And that’s the simple neural nets that I learned long ago and I’m sure there is more involved now.
  2. It’s very significant that the computer learns these rules on it’s own and could have huge resources, which can include huge quantities of data processing power, in doing so.
  3. Finally, what are you comparing with? One possibility is humans. Well, what do humans have that cannot be emulated with deep neural nets given time and resources (yes, I agree it will take some time)? The other possibility is that you are comparing with computational completeness. Here’s the only part that I am unsure of and where you might have a point worth investigating. I don’t know whether and how deep neural nets can be compared with computational completeness (going back to Turing). I’m don’t even remember exactly how to define computational completeness. But I can understand how the generality of computer algorithms might seem broader then deep neural nets in some way. It’s a good question to research.