Is There a Space for Machine Learning and Hardware?

I think what you're getting at here is a more expansive version of an idea that I think I've heard articulated in a lot of different ways. Sarah Hooker wrote the hardware lottery some time ago and for anyone who might be listening and kind of unfamiliar the basic idea is that ML algorithms didn't win necessarily by virtue of they're just being the best ideas but they happened to be a great fit for available hardware so transformers really took and exploited the parallelism available with GPUs. As a result they kind of became the workhorse of everything. There's this argument there that well if we have a more heterogeneous set of hardware backends that are easily available to use then you can expand

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