Julia's biggest success[es] so far?

I’m thinking of a) [enabling] commercial success and/or b) research success and/or c) good behind-the scenes package, likely at 1.0+. [And maybe Julia website in production?]

For a) you might not know of a specific company, and nothing might be obvious from looking at the public package repository.

However, I believe Pumas.AI (I believe part of COVID vaccine success) might be the largest success so far, a company built on SciML. Any other ideas?

DifferentialEquations.jl enables SciML, and is now under that umbrella. Note, I do not think general machine learning (e.g. Flux.jl) is yet a big success for Julia in the commercial sense, and even for use in research, could be wrong, at least not the mainstream SOTA research I follow. SciML is however not typical ML, and is a huge success.

SciML is a huge ecosystem, some of it rather new, e.g. ReservoirComputing.jl not yet at 1.0.

The first state-of-the-art Julia package was I believe JuMP.jl, but only recently after 10 years hit 1.0. I count it under b) research success and c), hopefully helped some companies too, likely wouldn’t/couldn’t know easily.

Genie.jl for building websites is now at version 4.18.0 whatever you want to read into that. [EDIT: It’s claimed ready for production, see from the horses-mouth below, so striking out repeatign incorrect claim to the contrary.]. It is used in production for intranet sites (for “billion dollar companies”), and also publicly open website.

Julialang.org however uses Franklin.jl for static website. It’s the most high-profile website run (in some sense) by Julia.

DataFrames.jl is now at version 1.3.3 a good candidate for c).

Is there a good way to filter the General registry for packages already at 1.0+? Anyone has code or can come up with, or maybe possible at juliahub.com?

Other Julia success companies I can think of:

Invenia is also a company built on mainly I think Julia with an impressive github: Invenia Technical Computing · GitHub

RelationalAI (likely not yet a commercial success).

Blackrock (not built on Julia originally, but adopted Julia, still using?), largest such company. Julia is also used in other finance companies, likely too new to for companies to build on it only.

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Can you please share the Reddit thread where I’d claim that Genie is not production ready? That’s certainly not true. I have personally developed quite a few apps for various consultancy clients and institutional customers, some of them being in production for years now (mostly backend/intranet apps though). In addition, I have collaborated with users and contributors that deploy Genie apps at work, some working at billion dollar companies. Not really at liberty to share details though, as it’s usually the case.

We’re now starting to put more effort to feature user apps on GenieFramework.com - but for an example of a great recent app that’s been running in production for over 3 months, with public access and public repo, people can check https://pkgs.genieframework.com for a good example of:

  • reactive data dashboard
  • with REST API
  • with SwaggerUI API
  • currently crunching 1,700,545 rows of package downloads data to compute stats in real time
  • on a puny 1GB RAM Heroku server (with some 1/2 of that RAM available)
  • with avg server response time of 500 ms
  • featuring lots of best practices including container/Docker deployments with prebuilt Julia sys img, caching, CDN support, MVC architecture, DRY, etc.

Version 4.18 means 4 breaking versions so far :slight_smile: But more importantly it’s about over 3-4 years of continuous improvements, over 1500 commits and some 60 awesome contributors. In addition, Genie 5 will be released in a couple of weeks, as our first performance focused release, which should address the concerns of some of the people in the Julia community around Genie’s speed.

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Well he wrote Genie “author” (I assumed you) claimed it and I responded, and he did yesterday respond repeating it for “Genie fella”, so it might be better if the denial came from you:

Cool, thanks. Who knows what he meant/understood. But yes, I’ll follow up, worth clarifying.

Here’s a short testimony by @Satvik about a commercial success that I bookmarked last year. It’s (probably deliberately) vague about the details but I found it impressive and convincing nonetheless.

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There’s probably about a billion dollars worth of predominantly Julia-based companies:

Putting on my Julia Computing hat, many more success stories using the language appear on our case studies page — even for folks that aren’t directly working with our company.

The foremost research project in my mind is the Clima project.

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Thanks for the mention! We’ve continued to move a lot of our Python code to Julia since then (and to write a lot of new Julia code), and have generally found that our average Julia code is 2-5x faster and more memory-efficient than our most optimized Python/numpy code.

One of the biggest gains was that Julia’s macro system allowed us to switch from calculating our features directly to building and evaluating a computational graph, which allowed us to skip a lot of redundant calculations. The fact that Julia’s for loops are fast also made it easy for us to do incremental updates, whereas in Python we’d essentially had to settle on batch refreshes every time we wanted new data.

I’m happy to go into more detail on any of these points, I just don’t know what people are interested in.

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Hi, I mentioned it recently in the other thread, however, as it is somehow related to this topic I’ll write about it here as well, in a slightly more serious way.

We are working on what I think is an interesting project. It’s about "Neural network analysis of uncertainty and sensitivity of deterministic and probabilistic models in conjunction with quantum computing approaches to shortest path optimization algorithms based on geometric algebra”. As for now it is a hobby project. It has a scientific and high performance computing focus. It is in an early stage which potentially gives particular opportunity to (early) team members to significantly shape the final outcome. And I would be happy to discuss any potential involvement, of course, if any of you is interested (please see below).

Based on my current assessment, I would say that potentially we are particularly strong in the area of quantum computing (very top world class experts). Moreover, should it come to this stage, I belive that the Board of Advisors would potentially consists of very experienced personalities from such areas as information technology, strategic management, finance and legal advisory. Personally, I do have research, information technology, investment banking and entrepreneurship background. Moreover, I have discussed it (I think I can say it) with a friend of mine who has (much more extensive than me) information technology and investment banking background.

In general, it is prudent to say that this kind of undertakings as described here are risky ones. However, I believe that the way I am currently structuring it, IMO, is not exposing any of the potential team member to excessive risks. It can be a hobby project, can be a bootstrapped project, can be a quick exit, can also be a long term engagement with a venture capital fund. As for now, it is a hobby project. One can be involved in it in her / his spare time. Should it be the last option, I think I can say that due to some reasons, I do hold good and very good relations with some of the top venture capital funds in Europe, The North America and Asia and since my early professional days this was my interest.

To sum up, I would encourage you to take this potential opportunity into a consideration. Should you find it interesting, we would be particularly happy to discuss the topic with persons who are knowledgeable in such areas as artificial intelligence (particularly reinforcement learning but not only), quantum computing and satellite technologies as well as in additional specific domains such as sensitivity and uncertainty analysis, shortest path optimization algorithms as well as in geometric algebra. I believe that also general Julia specialists / professionals might be interested in this topic.

How I see it is, in case of interest, please write me a short direct message through this forum. I will reply, provide my name and surname, my LinkedIn and a short document with a brief description and quite extensive list of literature. If you still like the topic, I will provide 30 pages long document and some additional short writings on this hobby project. I will also provide additional documents I prepared so far, they are in a form of my structured notes (300 pages long) and output of my Julia coding (some charts and stats on this topic - nothing too fancy - as I mentioned it several times in this forum I am not a professional coder / developer / scientist). If you have also any other suggestions please let me know - I am rather very open and keen to listen. If you prefer email as a form of communication, I will be happy to provide info in this form as well (after initial contact over a direct message on this forum). If email is the case, I would like to kindly ask you not to provide any corporate / institutional addresses at this stage.

Yeah, I think that’s it. Thank you for taking the time to read.

P.S.
As I see some hard numbers in this thread, as an additional info, one Company currently operating in the similar space to the topic of this hobby project had recently raised about USD 100m in Series A and is in a portfolio of a leading social and environmental impact venture capital fund. The other Company, also operating in similar space, had quite recently raised about USD 90m in Series D, is in a portfolio of a well know venture capital fund with over USD 100bn under management and is currently preparing for USD 1.2bn IPO.

Actually, just wanted to add that I would be interested in writing a research paper on my hobby topic. I am not a scientist, even though I’d be happy to try my best.

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