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 We have a [GitHub discussions](https://github.com/OpenMathLib/OpenBLAS/discussions/) forum to discuss usage and development of OpenBLAS. We also have a [Google group for *users*](https://groups.google.com/forum/#!forum/openblas-users) and a [Google group for *development of*](https://groups.google.com/forum/#!forum/openblas-dev) OpenBLAS. 
 
-## Donations
-
-You can read OpenBLAS statement of receipts and disbursement and cash balance on [google doc](https://docs.google.com/spreadsheet/ccc?key=0AghkTjXe2lDndE1UZml0dGpaUzJmZGhvenBZd1F2R1E&usp=sharing). A backer list is available [on GitHub](https://github.com/OpenMathLib/OpenBLAS/blob/develop/BACKERS.md).
-
-We welcome the hardware donation, including the latest CPU and boards.
-
 ## Acknowledgements
 
-This work is partially supported by
+This work was or is partially supported by the following grants, contracts and institutions:
+
 * Research and Development of Compiler System and Toolchain for Domestic CPU, National S&T Major Projects: Core Electronic Devices, High-end General Chips and Fundamental Software (No.2009ZX01036-001-002)
 * National High-tech R&D Program of China (Grant No.2012AA010903)
+* Chan Zuckerberg Initiative's Essential Open Source Software for Science program:
+    * Cycle 1 grant: [Strengthening NumPy's foundations - growing beyond code](https://figshare.com/articles/journal_contribution/Proposal_NumPy_OpenBLAS_for_Chan_Zuckerberg_Initiative_EOSS_2019_round_1/10302167) (2019-2020)
+    * Cycle 3 grant: [Improving usability and sustainability for NumPy and OpenBLAS](https://chanzuckerberg.com/eoss/proposals/improving-usability-and-sustainability-for-numpy-and-openblas/) (2020-2021)
+* Sovereign Tech Fund funding: [Keeping high performance linear algebra computation accessible and open for all](https://www.sovereigntechfund.de/tech/openblas) (2023-2024)
+
+Over the course of OpenBLAS development, a number of donations were received.
+You can read OpenBLAS's statement of receipts and disbursement and cash balance in
+[this Google doc](https://docs.google.com/spreadsheet/ccc?key=0AghkTjXe2lDndE1UZml0dGpaUzJmZGhvenBZd1F2R1E&usp=sharing) (covers 2013-2016).
+A list of backers is available [in BACKERS.md](https://github.com/OpenMathLib/OpenBLAS/blob/develop/BACKERS.md) in the main repo.
+
+### Donations
+
+We welcome hardware donations, including the latest CPUs and motherboards.
+
 
 ## Users of OpenBLAS
 
-* <a href='http://julialang.org/'>Julia - a high-level, high-performance dynamic programming language for technical computing</a><br />
-* Ceemple v1.0.3 (C++ technical computing environment), including OpenBLAS, Qt, Boost, OpenCV and others. The only solution with immediate-recompilation of C++ code. Available from <a href='http://www.ceemple.com'>Ceemple C++ Technical Computing</a>.
-* [netlib-java](https://github.com/fommil/netlib-java) and various upstream libraries, allowing OpenBLAS to be used from languages on the Java Virtual Machine.
+Prominent open source users of OpenBLAS include:
+
+* [Julia](https://julialang.org) - a high-level, high-performance dynamic programming language for technical computing
+* [NumPy](https://numpy.org) - the fundamental package for scientific computing with Python
+* [SciPy](https://scipy.org) - fundamental algorithms for scientific computing in Python
+* [R](https://www.r-project.org/) - a free software environment for statistical computing and graphics
+* [OpenCV](https://opencv.org/) - the world's biggest computer vision library
+
+OpenBLAS is packaged in most major Linux distros, as well as general and
+numerical computing-focused packaging ecosystems like Nix, Homebrew, Spack and
+conda-forge.
+
+OpenBLAS is used directly by libraries written in C, C++ and Fortran (and
+probably other languages), and directly by end users in those languages.
 
-<!-- TODO: academia users, industry users, hpc centers deployed openblas, etc. -->
 
 ## Publications