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289 points sandslash | 1 comments | | HN request time: 0.447s | source
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skwb ◴[] No.44451927[source]
It's hard to describe, but it's felt like LLMs have completely sucked the entire energy out of computer vision. Like... I know CVPR still happens and there's great research that comes out of it, but almost every single job posting in ML is about LLMs to do this and that to the detriment of computer vision.
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jgord ◴[] No.44452144[source]
yeah, see my other comment.

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
These might be used by LLMs but are likely built using RL or 'classical' ML techniques, tapping into the vast parallel matmull compute we now have in GPUs / multicore CPUs, and NPUs.
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1. pzo ◴[] No.44452659[source]
I thought there been a lot of progress in last 2 years. (Video) Depth Anything, SAM2, grounding Dino, DFINE, VLM, Gaussian splats, Nerf. Sure less than progres in LLm but still I would say progress accelerated with LLM research.