y'know what's cooler than Perlin Noise? Simplex Noise [1]! This is what is hinted at at the end of this article. Also invented by the same person to address issues in the original Perlin Noise function. It's not as popularly known because it was restricted by patent issues for so long but as of 2022 the patent has expired!
Simplex noise is nice because it's more efficient to calculate, especially for larger dimensions but it has a noticeably different look to it so it's not a drop-in replacement.
It's also rather more difficult to implement in 3+d because the mapping to the simplex space is not exactly intuitive.