Add Zygote, etc. to About Julia Lecture

[jstac]

On the Python side we have this lecture that motivates use of Python:

https://lectures.quantecon.org/py/about_py.html

It's about why rather than how. Perhaps the Julia side could benefit from such a lecture. I might not be the best person to do this, although I'm willing to have a go in a month or two if no one else has.

[arnavs]

You mean posting the benchmarking table isn’t enough? :)

But I think this is a good idea. I’ll take a crack at it soon, maybe. Things to talk about are “code that looks like math,” “easy access to mathematicians and hackers,” and maybe “accessibility to MATLAB emigres.”

[jlperla]

An update: For this, I am thinking we are better off waiting until http://fluxml.ai/Zygote.jl/latest/ is solid enough to add to the AD lecture and to organize the value of Julia around support for library composition and "differentiable programming" (https://fluxml.ai/2019/02/07/what-is-differentiable-programming.html) as the evolution of algorithmic differentiation.

Without explaining its ability to do things that others cannot, it is hard to make the case for a relatively inconvenient and somewhat niche language - however beautiful and clean the syntax may be.

The Zygote.jl crew tell me that it is about a month or two away.

[arnavs]

@jlperla I'm modifying this issue because of what you wrote at https://github.com/QuantEcon/lecture-source-jl/pull/693.