I feel the opposite, they really are focused on being a language that's great for AI and heterogeneous compute, since that's what Modular is focused on. But the features are attractive for other use cases, it has access to MLIR, compile time metaprogramming, easy and ergonomic SIMD, and soon GPU support.
So they can optimize code. The main theme is addressing two-language problem (single high & low level language). They want uniform language for cpu/gpu/whatever-pu. They can't have garbage collection. They need strict dataflow analysis with precise destruction points.
They're not trying to do everything. They don't care about stuff like Hindley–Milner inference, logic programming, relational algebra integration, tsx like html integration, functional purity, algebraic effects and dozens of other concepts. They just care about extending python so you don't need to use ffi to jump into c++/cuda for performance because language already supports high performance constructs.