Can you recommend some papers which fit those criteria?
- Score-Based Generative Modeling through Stochastic Differential Equations https://arxiv.org/abs/2011.13456
- Structured Denoising Diffusion Models in Discrete State-Spaces https://arxiv.org/abs/2107.03006
- Efficient and Modular Implicit Differentiation https://arxiv.org/abs/2105.15183
- Scalable Gradients for Stochastic Differential Equations https://arxiv.org/abs/2001.01328
- Bayesian Optimization with Unknown Constraints https://arxiv.org/pdf/1403.5607.pdf
- SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks https://arxiv.org/abs/2006.10503
- DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking https://arxiv.org/abs/2210.01776
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So not only can Meta use these cutting edge techniques in their products without needing to request permission from the implementer, they can also sell those derivatives to anyone and practically have full ownership over what was submitted. Furthermore:
> You assume all risks associated with the use of your User Content.
and
> For the avoidance of doubt, Meta Platforms does not claim ownership of User Content you submit or other content made available for inclusion via our Website.
So, if anything goes wrong, it is the implementer’s fault entirely, but Meta may freely profit from those submissions in any way they see fit.
Sure, this is a cynical reading of the ToS, but I’m assuming the ToS will only ever be used in Meta’s favor…