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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.

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Okay great.

Why does AI and heterogeneous compute need ownership and lifetime checks again?

These are really needed for low level pointer heavy code.

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.

Do you see my point that they are trying to do everything?

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.

Because writing a garbage collector to run on graphics cards is a thankless PhD class problem, even if technically possible, no one will adopt it.

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