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by mintone
713 days ago
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I've been bullish[1] on this as a major aspect of generative AI for a while now, so it's great to see this paper published. 3D has an extremely steep learning curve once you try to do anything non-trivial, especially in terms of asset creation for VR etc. but my real interest is where this leads in terms of real-world items. One of the major hurdles is that in the real-world we aren't as forgiving as we are in VR/games. I'm not entirely surprised to see that most of the outputs are "artistic" ones, but I'm really interested to see where this ends up when we can give AI combined inputs from text/photos/LIDAR etc and have it make the model for a physical item that can be 3D printed. [1] https://www.technicalchops.com/articles/ai-inputs-and-output... |
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1. 3D is actually a broad collection of formats and not a single thing or representation. This is because of the deep relation between surface topology and render performance. 2. 3D is much more challenging to use in any workflow. Its much more physical, and the ergonomics of 3DOF makes it naturally hard to place in as many places as 2D 3. 3D is much more expensive to produce per unit value, in many ways. This is why, for example, almost every indie web comic artist draws in 2D instead of 3D. In an ai first world it might be less “work” but will still be leaps and bounds more expensive.
In my opinion, the media that have the most appeal for genAI are basically (in order)
- images - videos - music - general audio - 2D animation - tightly scoped 3D experiences such as avatars - games - general 3D models.
My conclusion from being in this space was that there’s likely a world where 3D-style videos generated from pixels are more poised to take off than 3D as a data type.