It’s a bit time consuming but it makes paper reading a lot more fun.
I'll quote a snippet below:
“My biggest mistake when starting my doctoral research was taking a top-down approach. I focused my efforts on a handful of research papers on the frontier of my chosen field, even writing code to solve problems in these papers from day one. However, I soon realized I lacked many foundational prerequisites, making the first year exceptionally tough. What I should have done was spend 3-6 months dissecting the hell out of all the key research papers and books written on the subject, starting from the very basics (from my knowledge frontier) and working my way up (the bottom-up approach).”
https://www.youtube.com/watch?v=VXktVbeWAeM
https://www.youtube.com/watch?v=Tpb2rXtBos4
perhaps, with the advent of AI, one will be able to convert a current book into a more detailed book, and also a current book into a smaller book, so maybe this idea is even easier to implement than 4 years or so ago, before chatgpt (but after summarizers, which prompted the idea in my head).
I would humbly appreciate any feedback on the concept of parametric books, for now, it's just an idea, but it's a free one, anyone is free to implement it.
thanks in advance, for your comments on it.
With bottom up I always feel lost because I don't know what it's useful for, the relationships to other pieces of knowledge, etc.
However, the learning itself has to occur bottom-up. Especially in math. Math is a skill hierarchy, and if you cannot execute a lower-level skill consistently and accurately, you will not be able to build more advanced skills on top of it.
I wrote about this recently here if you're interested: https://www.justinmath.com/how-to-learn-machine-learning-top...
We don't give first graders an overview of differential equations and their applications when we start teaching them addition and subtraction.