Hey Boston Lisp

[Michael Bukatin]

I have been looking at Julia and its ecosystem in the last few months, and 
it is a very interesting experience. The language has full-strength Lisp 
macros, and full-strength multiple dispatch (so it is a full Lisp), while 
the user-facing syntax is not Lisp-like:

https://docs.julialang.org/en/v1/manual/metaprogramming/

So it's both a Lisp and a non-Lisp.

Generally speaking, people who creat Julia are consistently trying to "eat 
one's cake and to have it too", along multiple dimensions. Another axis is 
that the language is more flexible than Python, but is as fast as C. This 
is achieved via a very tasteful language design (the compiler is a normal 
competent LLVM compiler without miracles, it does not play any special 
role in this combination of expressiveness and speed).

I have also found Julia open-source software on github unusually readable 
and easy to understand (it also tends to be very compact).

The reason I was looking at Julia was that I was having an unusually 
flexible class of machine learning problems (a class of neural machines
which is based on processing complicated structured data streams, and on 
using "flexible tensors" with tree-shaped indices; so one can do much more 
with these neural machines than with traditional neural nets).

Even the most flexible Python frameworks, such as PyTorch, are too rigid 
for this class of problems, because they are oriented towards fixed 
multidimensional arrays ("tensors").

In this sense, Julia ecosystem seems to have a perfect fit, the Julia Flux
machine learning framework, which is specifically oriented towards maximal
flexibility and away from "tensors", while still being focused on high
performance:

https://github.com/FluxML/Flux.jl

So far I was mostly reading other people's code, and doing small-scale
explorations of my own (and creating publicly available notes in the 
process): https://github.com/anhinga/2020-julia-drafts

I think that what I am trying to do with Julia Flux should be doable
single-handedly (the tools seem to be that good), but I also hope to find
collaborators (a small team would be able to move really fast with this).

   - Mishka


On Tue, 14 Apr 2020, Jonathan Godbout wrote:

> Hey Everyone,
> I hope you're doing well and staying safe.
> Sorry for the long wait between messages.
> As Didier just said the ELS will be online, yay!
> 
> How's everyone doing?
> Fare, how's the startup, I miss the details.
> 
> Jon
> 
> 
>