I always look forward to the monthly JuliaComputing blogs, and I tend to point people to them (and e.g. the amazing case studies). They are usually readable.
In the latest September one there is mention of:
NeuralFMU: Towards Structural Integration of FMUs into Neural Networks - Tobias Thummerer, Lars Mikelsons and Josef Kircher
FMU is not explained in the title or abstract (nor JuliaComputing blog):
Keywords NeuralFMU, FMI, FMU, Julia, NeuralODE
I might be speaking for many people when Julia is the only recognizable term, if that. NeuralODE was new to me/all of us(?) not long ago.
It made me recall from Matt @mbauman we are all in a 1% exclusive club (those who just know how to program anything), from his amazing early (JuliaCon?) video. I wander how exclusive the more specific science/Julia language club is, or e.g. knowing about NeuralFMUs.
What I most like about Julia is that I’m constantly learning of new stuff, new areas of science and math. I can’t imagine any other programming language community/ecosystem having as much coverage and depth.
Not too long ago (or before Julia), I did not know what e.g. automatic differentiation was, and I admit reading about Julia could be intimidating. I like for people to also consider Julia the general purpose language that it is.
Also in the blog, e.g. “HackerRank CEO Vivek Ravisankar Says Julia’s Dynamism and Speed Makes Julia Better for High-Performance Machine Learning” and:
There’s also been a discussion about using Lua along with Julia.
News to me.