There's a company called VeriSIM life trying to make the physiological models mentioned in the post more accessible [1]. They apparently fit their models across a bunch of publicly available and proprietary data. I found some peer-reviewed publications (e.g. [2]), but I am not sure how widely they are used.
Simulations Plus has been building models on this data since 1996 and is one of the more popular vendors for prebuilt software for this modeling. There’s literally dozens of vendors with software though because companies have been working on this since the 80’s despite the article’s claim that this has been an ignored problem.
For me it would be, first and foremost, "not having to deal with Python's many idiosyncrasies". Even when I go with best-practices, trying to git clone a Python project and "pip install" something into a virtualenv, it's STILL hit-or-miss whether it conflicts with something else. It's a very janky experience and I don't like it, and this isn't even before touching the language itself, which is well-covered ground already: https://medium.com/nerd-for-tech/python-is-a-bad-programming...
Elixir is good at doing a lot of things at once on - scaling to lots of machines - and not exploding catastrophically while doing so.
Turns out this is really helpful for machine learning where you want to coordinate big data pipelines and do things like batching requests to a GPU resource (because GPUs want to be parallelized).
