Hi Ian, Python is an example of a language with solid package management and 
repository (Pypi), FFI, parallelism support (e.g. Dask), and data structures. 
Julia is another. They also both have extensive eco-systems for data science 
oriented tasks. Python has an extensive eco-system for many other things too.

>  Most of us learn to reason about optimization, monte-carlo methods, AI and 
> data mining by deep experience of one programming language.

I reason about those things in terms of mathematics and abstract structures: 
I'd venture to say that's par for the course because its easiest. Most 
implementations of staple algorithms on the other hand are C/C++ and it I don't 
think it has anything to do with convenience of reasoning in C. It is to do 
with portability, integration and performance.

I was drawn to J by the grammar. The infix / suffix notation and combination 
rules must lead to a different way of conceiving what verbs are useful, and 
perhaps to a different way of thinking entirely. It is inspired, and I remain 
extremely impressed by it. However, this must be separated from the utility of 
the language for a workload which is down to the suitability of the vocabulary 
it supports today and in the near future.
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