Hacker News Reader

Comment by jstx1 | Hacker News Reader

I don't see the value of a language-specific format when we have things like parquet.

The repo is pretty clear on its intentions to not be a language-specific format:

> Development Plans

> I fully intend to develop JDF.jl into a language neutral format by version v0.4. However, I have other OSS commitments including R's {disk.frame} and hence new features might be slow to come onboard. But I am fully committed to making JDF files created using JDF.jl v0.2 or higher loadable in all future JDF.jl versions.

It's beyond v0.4 and at v0.5.1 right now so it seems delayed, but the repo describes intentions to be a language-neutral format after the dust settles. I think we're just taking a snapshot too early in the timeframe to really know what this project is truly all about. And given that the author is an OSS dev for multiple languages, this intention makes a lot of sense.

I think Julia is one of those researcher languages like Haskell so it's probably just someone having fun, writing a paper, or whatever.

Julia is still niche, but it's definitely used in production?

The NY Fed have their main model of the economy in Julia (ported from Matlab)

this https://juliahub.com/case-studies/ny-fed/ ?

This:

https://frbny-dsge.github.io/DSGE.jl/latest/

Sounds like research to me? I dunno...

I don't agree with this. Julia does not have new ideas the same way Haskell does, and Julia has done a lot of work to be practical, like having a good way of calling Python and R code from early on in its life. If Julia has done anything new, it's probably related to being fast, but that's not exactly a novel idea.

Sure it does.

Have you seen the type system used to generically dispatch matrices to GPUs or cpus.

Or the dispatching to give you auto-differentiation?

Maybe it's not your definition of "new ideas", but they are really useful and original.

Julia is unique in using multiple dispatch pervasively. It did not invent multiple dispatch, but it certainly popularized it.

How come you never see anything practical made in Julia in production somewhere that isn't a pile of research mathematics? I personally can't think of a single tool or company. It's not like it's a young language either? I have seen dozens of niche papers written using it though.

Being fair, I have seen dozens of not hundreds of products and mass deployed projects written in similar languages. Even Haskell made its way to a lot of desktops in the Linux world, and Haskell is super niche research territory imo.

The clinical analysis for the COVID-19 vaccines was pretty practical and that was Pumas used by Moderna. There's a JuliaCon talk about that from the Director Head of Pharmacometrics at Moderna. There's Formula 1 usage, there's a some satellites running Julia onboard, etc. Some are documented here https://juliahub.com/case-studies/ though some people post what they are doing on the Discourse and Slack and so those end up being the most comprehensive source. Of course you can always argue whether 30 public examples is enough, or 50, or etc. but it's far from 0. And of course, most examples are never for public release.

Fifteen years ish and there's maybe ten-thirty production use cases that kinda can't be verified because they all sound like research projects doesn't sound super great to me. No offense, but I do wonder if all of those cases could have been accomplished more easily/sustainably with another tool and if they exist simply because someone was selling the language to a company as a contractor as a form of vendor lock in or something.

I guess I'll be curious once I install some software or an OS and see it brings in Julia in as a dependency or something. Otherwise I worry it's Matlab 2.0 with less of a mindshare...

Reply on news.ycombinator.com