Isn't Deep Learning more like Graph Theory? I shared yesterday that Google published a paper called CRISP (https://arxiv.org/pdf/2505.11471) that carefully avoids any reference to the word "Graph".
So then the question becomes what's the difference between Graph Theory and Applied Topology? Graphs operate on discrete structures and topology is about a continuous space. Otherwise they're very closely related.
But the higher order bit is that AI/ML and Deep Learning in particular could do a better job of learning from and acknowledging prior art from related fields. Reusing older terminology instead of inventing new.
So then the question becomes what's the difference between Graph Theory and Applied Topology? Graphs operate on discrete structures and topology is about a continuous space. Otherwise they're very closely related.
But the higher order bit is that AI/ML and Deep Learning in particular could do a better job of learning from and acknowledging prior art from related fields. Reusing older terminology instead of inventing new.