David K. Zhang

On a related note, `sum()` shouldn't work on lists of strings. Currently, `sum(["a", "b", "c"])` produces `"0abc"`.

You're right! Thanks, I had never noticed that Python fails to distinguish between `float`s and `int`s when used as `dict` keys; I have no idea where this is documented. Python...

Thanks for the find @haampie ! This is very mysterious to me. I haven't played with Julia/CUDA interop before, so I'm unsure how Julia code gets compiled for GPU execution....

Hey @kunyuan, thanks for your interest in **MultiFloats.jl**! No, this is not the expected accuracy, and I'm afraid to report I still don't understand what's going on with GPU `MultiFloat`...

Hey @nsajko, you're exactly right! The only special-cased arithmetic operators in **MultiFloats.jl** are `Float64xN * Float64`, and everything else is handled by Julia's numeric promotion system. I can certainly add...

Hey @haampie, thank you for bringing this to my attention! This looks like an unfortunate case where my lax approach to renormalization breaks things... At the moment I'm not sure...

Hey @nsajko, thanks for your interest in **MultiFloats.jl** and for putting this on my radar! The use of MultiFloats in ranges totally hadn't occurred to me, and this is something...

Hi @AwesomeQuest, thanks for your interest in **MultiFloats.jl**! This is very strange code in `Base`, and I don't understand why `Base.sincos` is implemented this way, either. For a workaround, you...

Whoops, accidentally closed in my last comment. I'll also add overloads for `sincos`, `sincosd`, and `sincospi` in the next patch release for **MultiFloats.jl**, which will automatically be defined when you...

Hey @haampie , I've unfortunately noticed the same issue. I've been able to get very simple loops like `@inbounds c[i] = a[i] + b[i]` to vectorize for `Float64x[2, 3, 4]`...