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> Who is going to make the scientific ecosystem? Google and apple. Apple already is working on a swift-numerics package. Look at TF python and jax. They've re

> Who is going to make the scientific ecosystem? Google and apple. Apple already is working on a swift-numerics package. Look at TF python and jax. They've re-implemented chunks of scipy and numpy twice, hired people to work on plotting (altair) etc And that's with python. Their engineering time will go much further with swift, obviously.

eigenspace 7y ago
Google and Apple are not going to make a full on scientific ecosystem because they don't have the domain experts or the motive. Numpy is not the same thing as scipy. DifferentialEquations.jl in julia is a great example of what it actually takes to make a real, competitive differentiation equation library. The sort of stuff that was built there requires a deep connection to the scientific and mathematics literature. Cash won't cut it. Another great example that'll resonate with physicists at least is things like ITensors.jl https://github.com/ITensor/ITensors.jl https://github.com/ITensor/ITensors.jl. Apple and Google are not going to make something like that.
- dklend122 7y ago
  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 7y ago
    > 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 7y ago
      JuMP (https://github.com/JuliaOpt/JuMP.jl 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 7y ago
        Absolutely, that's a nice point.
pjmlp 7y ago
Apple doesn't care for anything that doesn't work on their OS. Unless they show to be as committed Microsoft is with .NET Core, Swift will have the same support as Objective-C has had since NeXT days. As for Google, I still don't believe that they are that committed as well, Chris Lattner left, and SF4T appears more on Reddit and HN comments than on any kind of Tensorflow official communication channels. If it wasn't for the valiant effort of one single developer not employed from either of them, Swift for Windows wouldn't even exist. This is how committed both companies are.
- dklend122 7y ago
  Google hired that developer. "As for Google, I still don't believe that they are that committed as well, " They have any approximately 10+ person team, many of whom are new hires from apple etc. Even for Google that's a decent chunk of change.
  - pjmlp 7y ago
    Yes, they hired him, at the end of the race, after he has done everything on his own without any kind of Google support. On my book being committed, is paying for the race at the start. When TF4S delivers even the half of what ML.NET or Julia allows for on Windows including IDE, libraries and tooling support, today, and they actually start doing a bit more information then what gets given to Python, C++ and JavaScript then they are actually committed.

eigenspace 7y ago

Google and Apple are not going to make a full on scientific ecosystem because they don't have the domain experts or the motive. Numpy is not the same thing as scipy. DifferentialEquations.jl in julia is a great example of what it actually takes to make a real, competitive differentiation equation library. The sort of stuff that was built there requires a deep connection to the scientific and mathematics literature. Cash won't cut it. Another great example that'll resonate with physicists at least is things like ITensors.jl https://github.com/ITensor/ITensors.jl https://github.com/ITensor/ITensors.jl. Apple and Google are not going to make something like that.

dklend122 7y ago
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 7y ago
  > 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 7y ago
    JuMP (https://github.com/JuliaOpt/JuMP.jl 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 7y ago
      Absolutely, that's a nice point.

pjmlp 7y ago

Apple doesn't care for anything that doesn't work on their OS. Unless they show to be as committed Microsoft is with .NET Core, Swift will have the same support as Objective-C has had since NeXT days. As for Google, I still don't believe that they are that committed as well, Chris Lattner left, and SF4T appears more on Reddit and HN comments than on any kind of Tensorflow official communication channels. If it wasn't for the valiant effort of one single developer not employed from either of them, Swift for Windows wouldn't even exist. This is how committed both companies are.

dklend122 7y ago
Google hired that developer. "As for Google, I still don't believe that they are that committed as well, " They have any approximately 10+ person team, many of whom are new hires from apple etc. Even for Google that's a decent chunk of change.
- pjmlp 7y ago
  Yes, they hired him, at the end of the race, after he has done everything on his own without any kind of Google support. On my book being committed, is paying for the race at the start. When TF4S delivers even the half of what ML.NET or Julia allows for on Windows including IDE, libraries and tooling support, today, and they actually start doing a bit more information then what gets given to Python, C++ and JavaScript then they are actually committed.