Contrarily if you're doing something that doesn't map that well to tensor cores you have a problem: every generation a larger portion of the die is devoted to low/mixed precision mma operations. Maybe FGPAs can find a niche that is underserved by current GPUs, but I doubt it. Writing a cuda/hip/kokkos kernel is just soo much cheaper and accessible than vhdl it's not even funny.

AMD needs to invest in that: Let me write a small FPGA kernel in line in a python script, compile it instantly and let me pipe numpy arrays into that (similar to cupy rawkernels). If that workflow works and let's me iterate fast, I could be convinced to get deeper into it.