The reason CUDA has won is precisily because it isn't horribly stuck in a C dialect, have embraced polyglot workloads since 2010, have a great developer experience where GPUs can be debugged like regular CPUs, and the library ecosystem.
Now while NVidia is making standard C++ run on CUDA, Intel is still having SYSCL and oneAPI extensions.
Similarly with Python and RAPIDS framework.
Intel and AMD have to up their game for the same kind of developer experience.
Err.. Last time I checked, CUDA was the one with the partially compliant C++ implementation, while, on the contrary, SYSCL was being base on pure C++17..
Time to check again, as CUDA is C++20 for a bit now (minus modules), and NVidia is the one driving the senders/receivers work for C++26, based on their CUDA libraries.
SYCL isn't pure C++, meaning writing STL code that goes into the GPU, like CUDA allows for, nor requires the hardware to follow C++ memory model.
Now while NVidia is making standard C++ run on CUDA, Intel is still having SYSCL and oneAPI extensions.
Similarly with Python and RAPIDS framework.
Intel and AMD have to up their game for the same kind of developer experience.