so DeBeers just buys up all the labs that grow them and still have a monopoly. Lower the price competition appears and raise the price when competition goes bankrupt. Sort of like Amazon.
The process to make diamonds is open to anyone and has a lot of industrial uses apart from jewelry so not possible for Debeers to monopolize the market they can crash the prices but increasing prices won't be possible.
PyPy performs valiantly compared to Cpython -- even better than LuaJIT. I'm sure someone skilled at writing it could do an even better job.
I measured 3 Mojo implementations. The first is a dynamic implementation, it performs like a typical dynamic language. Then when you use Mojo's SIMD intrinsics you can get compiled-tier performance in line with Futhark, Julia, Rust etc.
Then if you use their Max toolchain you can compile Mojo directly to Metal, with performance at the top of the stack (for the amount of money Qualcomm paid they'd better be there!).
The Rust / Mech version was rewritten to put it back on top, but the unchecked test is about equal. Basically if a toolchain can emit direct Metal code there's nothing preventing equal performance it seems, so the magic is in the compiler. Although there is some abstraction overhead depending on how you get there e.g. going wgpu->Metal has a penalty over going directly to Metal.
The big disclaimer again is that all of these measurements should be taken as lower bounds for one algorithm on one machine. I'm sure expert performance engineers could do better.
EVs are some of the cheapest cars you can get. All of the American manufacturers sell them at a huge loss, due to government regulations around average mpg for their lineups, etc
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