Although that's true, TruffleRuby and GraalPy show that you can actually make highly dynamic languages extremely fast with a powerful enough JITC, which Graal/T

Although that's true, TruffleRuby and GraalPy show that you can actually make highly dynamic languages extremely fast with a powerful enough JITC, which Graal/Truffle actually are. The hard part those projects are wrestling with is being 100% compatible with the entire ecosystem, warty native modules that abuse interpreter internals and all the rest. But they have the tech and manpower to do it. So one of the key questions for Mojo is going to be this: how does it or will it compare to GraalPy as it matures, which should be able to run untyped Python at high speed, potentially even multi-threaded, with existing native extensions. It can be that maybe the advantage is predictability, lack of warmup, that people in the AI space just prefer stuff made by a startup, that Mojo solves other pain points like packaging, all sorts of things. But it can also be that Python took off in ML exactly because it's untyped and people don't want to deal with the hassle of a type system if they don't need to. The alternatives section of the blog post doesn't mention Graal/Truffle at all, suggesting that this is a bit of a blind spot for them. But these are well funded projects that have already yielded many-orders-of-magnitude speedups for existing code. It's not necessarily a good idea to write them off.