Flux <3 NumFOCUS
We are very excited to announce that FluxML is partnering with NumFOCUS as an affiliated project to further the cause of open and reproducible science and growing the adoption of the FluxML ecosystem. Flux has always had the mission of being a simple, hackable and performant approach to machine learning, which is extended to a number of domains in science by means of differentiable programming.
This milestone is the result of the coming together of the Julia community to support the vision of producing high performance machine learning tools which are flexible towards the needs of novel use cases such as: graph neural networks, scientific machine learning, and differentiable programming. The support of the community as well as the contributions made to that end have helped catapult Flux to this stage, so we want to take this moment to thank the Julia community for their continued support, guidance, and encouragement.
This partnership will help us in growing the community, bringing new contributors into the ecosystem, and help us manage the funds from future grants we raise for a number of upcoming projects - be they compiler related tools for our AD, or support for low precision math on GPUs in a flexible and generic manner.
We hope to announce a lot more exciting news in the times to come and thank you all so much once again for helping us reach this exciting milestone in our journey! There is a lot more that we want to do, and this is definitely only the start.
About NumFOCUS: The mission of NumFOCUS is to promote open practices in research, data, and scientific computing by serving as a fiscal sponsor for open source projects and organizing community-driven educational programs. NumFOCUS is a 501(c)(3) public charity in the United States.