[joe_the_user]

What tools are there?

Github implementation of current hot papers seems like a good approach. A lot of papers don't come with source code and creating source is useful thing to community.

Blogs explaining the mechanics of a paper.

A graduate degree in CS or Math might help.

If you could do a series of blogs that together are enough to introduce a new person, that could get interest.

[thisisit]

Are there any good reference (blogs, github profiles, forums) for highlighting current hot papers, their implementation or explaining the mechanics?

[gfredtech]

check out Stanford Scholar[1], they create talks on hot research papers(not only ML/AI) and then try to explain the papers the intuition and technicalities of the paper, most of the talks are translated to other languages as well

[1]: https://scholar.stanford.edu

[eastWestMath]

You'd probably need to spend a few years learning the basics first...

[thisisit]

Agreed.

Sometimes imitation is the best way to learn. So if there are some great resources for source codes being derived from papers, it will help people how to read papers and create code out of it.

[eastWestMath]

I mean, you probably need to look at a few textbooks before you'll make any sense of papers.