[__erik]

I'm really excited for this. I'm unaware of any mainstream language with first class support for differentiation, I think its going to be really interesting to see what people use it for out side of ML.

[adamnemecek]

Julia is in the same space.

[taliesinb]

Yup, work is continuing apace with Julia’s next-gen Zygote project.

Also, from the GP’s thought about applications beyond DL, my favorite examples so far are for model-based RL [1] and Neural ODEs [2]

[1] https://fluxml.ai/2019/03/05/dp-vs-rl.html

[2] https://julialang.org/blog/2019/01/fluxdiffeq

[__erik]

Julia is great but it doesnt play in the domain of apps and servers

[byt143]

Yes it does. See genie.jl for a full mvc framework. Also there's mux.jl and http.jl.

[mark_l_watson]

It does. I spent several evenings writing little bits of Julia code that do “non numeric” stuff like querying RDF data stores, text processing, etc. I think Julia is a reasonable general purpose language.

[ddragon]

It does have a ton of numerical/data science/general science libraries to be differentiated and to add value to the differentiable code though.