[magicalist]

> How so? First, kernel writing (or ML engineering more broadly) is a highly specialised task. Not everyone can do it. It shows that models are getting better and better at (easily verifiable) hard tasks.

No it doesn't. You have no idea how optimised the underlying kernels already were. If a kernel was already optimal, it doesn't matter if you bring a brain the size of a planet, you're not going improve it.

> Second, 20% gains in inference today gives better end results (i.e. lower overall cost) than 1% in training 2 years ago

Your claim (at least in implication) was some kind of trend here. It doesn't matter which one was better to optimise because it "gives better end results" if you're trying to make a trend line out of two unrelated things.

I'm looking for more efficient ways to pack items into packaging. You're looking for more efficient ways to dispatch workers. I report how much faster I can get a shipping container loaded. You report how much less it costs to to get powerlines fixed during a storm.

It's a bad comparison.