If anyone knew this we would be created AGI already. Probably scale issues and some new ideas on top of deep learning.

I would start with learning programming very well. On the side you can learn necessary math on school and from youtube. For calculus i recommend professor Leonard. If you dont have good foundations he start from i guess literally adding numbers. You will need good software skills anyways and you can do it without math. Create a website to show your future projects. Solve some programming problems in codewars etc. Programming language is not that important you just need to get used to abstract thinking. You can embed some AI models from OpenAI etc. to your website with their public API's.

When you know enough calculus, you can dive into ML theory with good skills in your belt. Eventually you can implement research papers and become a research engineer to work on cutting edge development in ML world. When you know some calculus i suggest you to watch Tesla AI ex-Lead Engineer Andrej Karpathy's lectures, he also briefly mentions relevant calculus. Before Karpathy i recommend you neural nets from scratch series in youtube.

Can I implement NECSTransformer architecture from this paper practically? What do you think?