![So I've just discovered if I use Super Mascot Draven Jax that I usually Don't Lose so hey enjoy it before the nerf : r/TeamfightTactics So I've just discovered if I use Super Mascot Draven Jax that I usually Don't Lose so hey enjoy it before the nerf : r/TeamfightTactics](https://i.redd.it/r918mwpws46a1.jpg)
So I've just discovered if I use Super Mascot Draven Jax that I usually Don't Lose so hey enjoy it before the nerf : r/TeamfightTactics
![Common Computer Sponsored 'CLIP+NeRF Team' Wins Second Place at Hugging Face x Google-Hosted Jax/Flax | by AI Network | AI Network | Medium Common Computer Sponsored 'CLIP+NeRF Team' Wins Second Place at Hugging Face x Google-Hosted Jax/Flax | by AI Network | AI Network | Medium](https://miro.medium.com/v2/resize:fit:1400/1*7vLUnnxnPZUHQvFIhYoAaQ.png)
Common Computer Sponsored 'CLIP+NeRF Team' Wins Second Place at Hugging Face x Google-Hosted Jax/Flax | by AI Network | AI Network | Medium
GitHub - soumik12345/nerf.jax: A minimal TPU compatible Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis.
![Massive Jax nerfs hit League of Legends PBE patch 13.4 cycle: E AP ratio reduced, health growth increased, and more Massive Jax nerfs hit League of Legends PBE patch 13.4 cycle: E AP ratio reduced, health growth increased, and more](https://staticg.sportskeeda.com/editor/2023/02/aecb8-16763815926911-1920.jpg?w=840)
Massive Jax nerfs hit League of Legends PBE patch 13.4 cycle: E AP ratio reduced, health growth increased, and more
![PDF] Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields | Semantic Scholar PDF] Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/21336e57dc2ab9ae2171a0f6c35f7d1aba584796/16-Table6-1.png)
PDF] Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields | Semantic Scholar
![Jon Barron on X: "JaxNeRF! Today we're releasing Google's internal JAX implementation of NeRF. Training goes from 3 days to 2.5 hours (on a TPU pod), PSNR is slightly higher(?!), and it Jon Barron on X: "JaxNeRF! Today we're releasing Google's internal JAX implementation of NeRF. Training goes from 3 days to 2.5 hours (on a TPU pod), PSNR is slightly higher(?!), and it](https://pbs.twimg.com/media/Eoqx9KNVgAA7DHJ.jpg:large)