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Convolutional neural nets work operate on low level structure and do high-level structure largely by stacking together low-level structural processing. The "ri
by AbrahamParangi 7y ago
Convolutional neural nets work operate on low level structure and do high-level structure largely by stacking together low-level structural processing.
The "right way" to do high-level structure for images is a fruitful active area of investigation which I expect will probably be tackled in the next 18 months.
- lonelappde 7y agoI don't think it's possible to do without learning a hidden 3D model from 2D data. It's nonsense to learn 2D projections directly from 2D projections, because small errors in the 2D projection can become catastrophic errors in the 3D model that humans use to interpret a 2D photo.
- jvanderbot 7y agoLearn maybe. But its easy to construct 3d information from 2d observations. See structure from motion, shape from shadow, Voxel carving, and even orbit determination.
- fooker 7y ago>18 months. Bold prediction. I wouldn't be surprised if this is an open problem in 18 years.
- AbrahamParangi 7y agoI'll go further: For each problem there are a few sub-problems and a "right way" to do each of them where a "right way" corresponds to an algorithm which efficiently tackles some element of the implicit structure of the problem. I think within 5 years we will have made great progress on algorithmically discovering these "right ways" across many problem domains. I think both differentiable neural architecture search[0] and the MAML with implicit gradients[1] stuff is very interesting from this perspective. [0]https://arxiv.org/abs/1905.13577 https://arxiv.org/abs/1905.13577 [1]https://arxiv.org/abs/1909.04630 https://arxiv.org/abs/1909.04630