Unpopular answer: Meh. I see your point, but we are already using specialized algorithms to solve problems on generic hardware (CPU). You can move to different

Unpopular answer: Meh. I see your point, but we are already using specialized algorithms to solve problems on generic hardware (CPU). You can move to different generic hardware (GPU/OpenCL/...) which might be better suited (depending on the problem), or use/rent more generic hardware on demand (cloud computing). What you're implying is already happening, using/programming "generic" FPGAs to act as specialized accelerators seems to be slowly trending (e.g. Xilinx UltraScale); and if that's working well, "larger" process nodes seem to be getting cheaper these days (e.g. >= 45nm ASICs). But as far as I am aware the tooling and ecosystem for all this is still pretty bad; especially compared to how C/C++ compilers came a long way, JS's ease of accessibility or python's trove of libraries. (Disclaimer: I am not working in that field, so I might be outdated). So to refine you suggestion: Improving the eco system around hardware synthetization could be a thing? However, that doesn't seem to be what user richtapestry was thinking of(?).