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Cheers, and great question! FPGAs are pretty amazing devices, but one thing that's been holding them back is how difficult they have been to work with. Typically to actually make use of an FPGA you'd need to have an FPGA expert and an embedded software engineer on your team, along with all the requisite tools and materials.

That has started to change dramatically in the last decade, with open source FPGA toolchains like yosys, runtimes like the PYNQ framework and RTL generator tools like Tensil being developed. When you put these things together, working with FPGAs starts to become as easy as using any other compute platform. For that reason, I think there are lots of applications involving FPGAs that will soon be invented to take advantage of this trend. One could speculate that the reason Intel and AMD are buying up FPGA vendors is because they see the potential there.

As far as head-to-head comparisons go, as long as you're running the workload it was designed for in the environment it was designed for, an ASIC will always be the best possible perf per watt. The question is what happens when you go outside those bounds. Can you take your model, swap out a layer, and have it run just as fast on your Coral or NPU? Probably not, at least right now. But with Tensil, you can re-run your architecture search to find the best accelerator, and take advantage of it right away.