So I came across these 2 questions:

 - [Ideas on how to make a neural net learn how to split sequence into sub sequences][1]
 - [Search minimum value with learning machine algorithm][2]

For me both problems could be solved easily using traditional algorithmic techniques (as in coding in your typical programming language. I assume that training a NN (or any other machine learning technique) for such sorts of problems will be more time consuming, resource intensive and pointless.

My question is: If I want to solve a problem, how to decide whether it is better to solve algorithmically or by using NN/ML techniques? What are the pros and cons? How can this be done in a systematic way? And if I have to answer someone why I chose a particular domain, how should I answer?

**Summary:** Choosing between normal computational approach vs abstract approach used in Neural Nets or ML or AI.

Example problems are appreciated :)

  [1]: https://ai.stackexchange.com/questions/5838/ideas-on-how-to-make-a-neural-net-learn-how-to-split-sequence-into-sub-sequences
  [2]: https://ai.stackexchange.com/questions/4859/search-minimum-value-with-learning-machine-algorithm/4860#4860