ONNX is pretty old at least 5 years and its still mostly useful on Nvidia GPU's or x64 CPU.
TBH. cool that projects like that are still alive but MLIR looks like the future of proper model storage, and custom format and loading is still a king today cause you can easily modify model and optimise or even fine tune which isn't even possible in ONNX without ton of work (also static spec and versions in protobuf sucks wish they migrate to flatbuffers).
for people looking at deploying ML: this comment is not even wrong[1], there's no real way to respond to it substantively. It's sort of like saying Swift came out 7 years ago and it's mostly useful for iPhone X and the first iPad Air.
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ONNX is pretty old at least 5 years and its still mostly useful on Nvidia GPU's or x64 CPU. TBH. cool that projects like that are still alive but MLIR looks like the future of proper model storage, and custom format and loading is still a king today cause you can easily modify model and optimise or even fine tune which isn't even possible in ONNX without ton of work (also static spec and versions in protobuf sucks wish they migrate to flatbuffers).
for people looking at deploying ML: this comment is not even wrong[1], there's no real way to respond to it substantively. It's sort of like saying Swift came out 7 years ago and it's mostly useful for iPhone X and the first iPad Air.
[1] https://en.wikipedia.org/wiki/Not_even_wrong
Ok :)