The work McGrath discusses aims to determine how much neural networks respect the manifold hypothesis.

“huge vector then most like most natural images are sort of multi-colored static the natural images sorry most most images in this space like if i just pick a point it's like multi-colored static natural images are like a tiny fraction of this and they're sort of close to each other um i think what we're doing is trying to like pull that manifold hypothesis into to like to what extent do do neural networks respect the manifold hypothesis”