JonathanFly

18 ms·

1. 151.▲
   by JonathanFly 7y ago

   In particular https://twitter.com/jonathanfly/status/1176355623857991681
2. 152.▲
   by JonathanFly 7y ago

   This is a neat idea, but the execution was kind of minimum-viable-attempt. You can do this yourself though, just google some famous paintings with X-RAY images and try it. I doubt this is very accurate but it is fun. I posted a few https:&
3. 153.▲
   by JonathanFly 7y ago

   > It seems like the input images that you used are paintings. Yeah, I love trying things that aren't supposed to work! They often do work and surprise you, or fail in interesting ways.
4. 154.▲
   by JonathanFly 7y ago

   Not bad but monocular depth estimation has gotten pretty good all around. I made these similar images with basically no expertise, no manual mapping, just trying random single image depth projects from github. I kind of just went with whate
5. 155.▲
   by JonathanFly 7y ago

   >The best part was that there was zero quality control, because anyone could edit anyone's map, so you constantly encountered variations and remixes of popular maps. Apart from a handful of very popular main maps, you often had no i
6. 156.▲
   by JonathanFly 7y ago

   >It is entirely possible to build a useful AR/MR/VR map of any indoor space using the Apple U1 chip in just a few minutes few minutes. I'd love to see the fidelity of this. It seems unbelievable...
7. 157.▲
   by JonathanFly 7y ago

   Imagine a future where 'this abstract was generated by the model' is in the training material for future papers https://twitter.com/jonathanfly/status/1171551688668471297
8. 158.▲
   by JonathanFly 7y ago

   I read that meaning you can start with the actual pre-trained GPT-2 models but I never got an answer when I specifically asked if that was the case.
9. 159.▲
   by JonathanFly 7y ago

   I haven't look into at all myself, but he also said: >We do provide training code that should work out of the box for gpt2 117M/345M https://twitter.com/TheRealRPuri/status/1161319745259393024
10. 160.▲
    by JonathanFly 7y ago

    On the NVIDIA GPT- 2 implementation: >What would be the largest model one could train across 2x 2080Ti? >~800M gpt2. this is largely due to the memory required to House parameters + optimizer states. If one uses a smaller optimizer th
11. 161.▲
    by JonathanFly 7y ago

    I did some tests on this, trying to find footage I thought would be least well suited to interpolation: https://twitter.com/jonathanfly/status/1156343739738152961 https://www.youtube.com/watch?v=FR
12. 162.▲
    by JonathanFly 7y ago

    I tried to make full cards, text and cart art and card structure, all in the same model but it didn't work: https://twitter.com/jonathanfly/status/1124918657220534272 This person trained a nice cart art model