To me its totally obvious that we will have a plethora of very valuable startups who use RL techniques to solve realworld problems in practical areas of engineering .. and I just get blank stares when I talk about this :]
Ive stopped saying AI when I mean ML or RL .. because people equate LLMs with AI.
We need better ML / RL algos for CV tasks :
- detecting lines from pixels
- detecting geometry in pointclouds
- constructing 3D from stereo images, photogrammetry, 360 panoramas
==> For me it is more something like :
Source = crude video-or-photo pixels (to) ===> Find simple many rectangle-surface that are glued together one another.
Similarly I use another algo to detect pipe runs which tend to appear as half cylinders in the pointcloud, as the scanner usually sees one side, and often the other side is hidden, hard to access, up against a wall.
So, I guess my point is the devil is in the details .. and machine learning can optimize even further on good heuristics we might come up with.
Also, when you go thru a whole pointcloud, you have a lot of data to sift thru, so you want something fairly efficient, even if your using multiple GPUs do do the heavy matmull lifting.
You can think of RL as an optimization - greatly speeding up something like monte carlo tree search, by learning to guess the best solution earlier.