On: Julia 1.4

[dklend122]

It's not JUST google and apple, I'm sure they have enough cash and expertise and will to create enough momentum to attract more domain experts in other areas. Especially once google brain and deepmind start working on things more complex than stacking layers, which is happening now.

In particular, do you have another example aside from DifferentialEquations.jl ?

Neural ODEs are hot enough that something like that could easily pop up in swift.

ITensors is interesting, but that's only one.

[eigenspace → dklend122]

> It's not JUST google and apple, I'm sure they have enough cash and expertise and will to create enough momentum to attract more domain experts in other areas.

Maybe, but I'm doubtful. Scientific domain experts flock to languages like Python, Julia, Matlab, R, etc. because they're interactive and allow them to quickly iterate on ideas, query data, produce plots, etc. Swift is not much of an interactive language and is not built around that kind of repl driven experience.

> In particular, do you have another example aside from DifferentialEquations.jl ?

Sure, here's a smattering of high quality packages made by and for research scientists:

    https://github.com/JuliaApproximation/ApproxFun.jl
    https://github.com/BioJulia
    https://github.com/JuliaDiffEq/ModelingToolkit.jl
    https://github.com/crstnbr/MonteCarlo.jl
    https://github.com/chriselrod/LoopVectorization.jl
    https://github.com/JuliaNLSolvers/Optim.jl
    https://github.com/PainterQubits/Unitful.jl
    https://github.com/mcabbott/TensorCast.jl
    https://github.com/JuliaPhysics/Measurements.jl
    https://github.com/Jutho/TensorOperations.jl

There are many many more, these are just the first that came to mind.

[newen → eigenspace]

JuMP (https://github.com/JuliaOpt/JuMP.jl) for optimization is really nice and I don't think there is an equivalent this good in another language.

[eigenspace → newen]

Absolutely, that's a nice point.