Unraveling complexity: building knowledge, one paper at a time
From the perspective of AI(especially the generative model).
We will be happy if there is a domain with a lot of accessible data(like language, pictures, proteins).
We will be happier if we manage to find a good way to represent the data(like a vector for a word, a matrix for a picture).
We will be even happier if we can label each single data(this is a good answer in a dialog, this is a smiling/crying face).
If all the conditions were satisfied, conditional generative models can be used to understand these data, including finding the distribution and generating some entirely new data under some human desire(condition).
I'm happy to see that over years protein domain has overcome many difficulties to reach todays result, in my memory(if I remember correctly) some years ago they were struggling to find a good representation of a protein structure.(I roughly looked at the paper, in this paper it seems that they proposed a new method to represent a peotein, it may be helpful to other researchers in this domain).