A lot of relationships are (locally) linear so this isn’t as restrictive as it might seem. Many real-life productionized applications are based on it. Like linear regression, it has its place.
T-SNE is good for visualization and for seeing class separation, but in my experience, I haven’t found it to work for me for dimensionality reduction per se (maybe I’m missing something). For me, it’s more of a visualization tool.
On that note, there’s a new algorithm that improves on T-SNE called PaCMAP which preserves local and global structures better.
https://github.com/YingfanWang/PaCMAP
