“Derivative products include any output derived from Stability AI's Foundational models, such as fine-tuned models or other creative outputs,” a spokesperson from Stability AI told Decrypt. “Examples of derivative works include SD3 fine-tunes, LoRA fine-tunes, adapters etc. and these can also be trained with SD3 output images.”
The license also says that “you are the owner of derivative works you create, subject to Stability AI’s ownership of the Stability AI materials and any derivative works made by or for Stability AI.” In other words, as long as those boundaries are respected, fine-tuning and profiting from it should not be against the terms and conditions.
“To safeguard our IP, it is not permitted to train new foundational AI models using SD3 outputs as training data, and all activity must adhere to our acceptable use policies,” the company spokesperson told Decrypt.Researchers at ETH Zurich develop the fastest possible flow algorithmCOMPUTER AND INFORMATION TECHNOLOGYRESEARCHRasmus Kyng has written the near-perfect algorithm. It computes the maximum transport flow at minimum cost for any kind of network – be it rail, road or electricity – at a speed that is, mathematically speaking, impossible to beat.
IEEE Symposium on Foundations of Computer Science (FOCS) 2024. external pagehttps://focs.computer.org/2024/accepted-papers-for-focs-2024/call_made
Chen, L, Kyng, R, Liu, YP, Meierhans, S, Probst Gutenberg, M. Almost-Linear Time Algorithms for Incremental Graphs: Cycle Detection, SCCs, s-t Shortest Path, and Minimum-Cost Flow. Proceedings of the 56th Annual ACM Symposium on Theory of Computing, June 2024 (STOC 2024). doi: external pagehttps://doi.org/10.1145/3618260.3649745call_made.
Chen, L, Kyng, R, Liu, YP, Peng, R, Probst Gutenberg, M, Sachdeva, S, Kyng, R. Maximum Flow and Minimum-Cost Flow in Almost-Linear Time. 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS), Denver, CO, USA, 2022. doi: external page10.1109/FOCS54457.2022.00064call_made.
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