Incredible post. I laughed when I saw the title, snickered at the first paragraph, and then proceeded to be blown away by the rest of it. Thought I was in for a joke and instead I'm thinking about the nature of ML Ops and what it's become.
My sentiment exactly. The premise of the article comes across a little naive because there are so many fine-tuned libraries for specialized hardware architectures that already do this computation very efficiently.
However, it did make me wonder what this might look like on a gpu-accelerated database engine that is designed to leverage the SIMD parallelism of GPGPU architectures.
Beyond using SQL/NoSQL databases for CRUD apps I am not a "database guy", so I'm not sure about the feasibility, but it would be interesting to see it implemented.
