@ddragon described it rather well. Some significant examples include JuMP (https://jump.dev https://jump.dev) for mathematical optimization and how FluxML (Juli

@ddragon described it rather well. Some significant examples include JuMP (https://jump.dev https://jump.dev) for mathematical optimization and how FluxML (Julia's "Keras"), Zygote (whole program automatic differentiation) and ODE solvers can work together easily to build Neural ODE solvers in relatively few lines of code. It is also why one person can write - https://github.com/yuehhua/GeometricFlux.jl https://github.com/yuehhua/GeometricFlux.jl - and benefit from the CUDA, FluxML, Zygote packages to get high performance.