I have some questions about SVM : 1- Why using SVM? or in other words, what causes it to appear? 2- The state Of art (2017) 3- What improvements have they made?
SVM works very well. In many applications, they are still among the best performing algorithms.
We've seen some progress in particular on linear SVMs, that can be trained much faster than kernel SVMs.
Read more literature. Don't expect an exhaustive answer in this QA format. Show more effort on your behalf.