Julia is powering the next wave of biomedical, machine learning, and climate startups
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A whole new ecosystem of companies are coming to the limelight and they all have one thing in common: they are building with the Julia programming language. Companies operating at the edge of what is possible are relying on Julia’s computational efficiency, ease of use, and purpose built nature in the scientific computing ecosystem to solve some of the worlds most challenging problems.
In this article, we will explore the benefits of Julia and talk about some of the startups using Julia to change the world. Let’s dive in!
Before we talk about why companies are using Julia, it is good to get a sense of the breadth and depth of the different organizations building on the Julia ecosystem.
Startups using Julia extensively:
- Genie Cloud
- Quera Computing
- Invenia
- Julia Computing (now JuliaHub)
- Beacon Biosignals
- RelationalAI
- PumasAI
- Julius Technologies
- Zapata
- Zipline
- Find more: https://juliahub.com/case-studies/
You can find talks at previous JuliaCon’s from many of these organizations.
Large organizations using Julia (not exhaustive):
- AWS (Quantum Computing)
- Microsoft Research
- Apple (Autonomous Systems Group)
- NASA
- AMD
If you are looking to join a company using Julia, you might want to check out this article I wrote on getting a job using Julia:
Startups typically operate in competitive spaces. Spaces usually dominated by large players like Google, AWS, or Microsoft (in the case of the cloud). In order for new companies to fight against these incumbent players, they need something radically different that what these larger companies are doing.
For many startups, this means using the Julia programming language. Julia’s ease of use, strong community, expanding ecosystem, and speed make the language a natural choice. I have said it before but I will say it again, those individuals and companies betting big on Julia now are the people who will garner a disproportionate amount of the upside. Right now, this is manifesting itself in the talent domain. 2022 was a huge year for hiring and companies like RelationalAI and JuliaComputing have continued to snap up tons of key Julia ecosystem contributors.
There is also a strong desire from the community to see these companies succeed as they are often time started by Julia contributors themselves like Beacon Biosignal. These companies can also tap into the community on Discourse and Stack Overflow which are (in my opinion) some of the most responsive and helpful communities in the world.
Julia is a high-level language, which means it can be used to quickly develop prototypes and solve problems without needing too much code. This makes Julia extremely useful for startups as they can rapidly develop their products or services without having to worry about complex coding requirements. Additionally, since Julia is open source, there are plenty of packages that you can use in order to make developing even faster.
One of the original goals of Julia was to create a tight loop for developers between prototypes and production ready applications. With Julia, that loop is significantly reduced since you can usually just write your code once and not have to switch languages for production. It’s worth saying that this is an ideal case, if you do things that don’t scale with (deeply nested loops or poorly designed code), you will still run into issues going into production but at least you can refactor in one language.
One of the biggest draws of using Julia is its compatibility with other languages such as Python, R, C++, MATLAB and Java. This allows you to easily integrate these languages into your development process without having to write extra code or invest in additional resources. For example, if you need to use Python for certain tasks but want the speed of C++ for others, you can easily combine them together in your project with Julia.
Companies like Julius Technologies are working on bridging the gap between multiple languages with Graph Computing and Julia:
If you want to see a Python and Julia integreation in action, check out how simple it is in this article:
Julia also offers flexibility when it comes to its platforms; it supports Windows, Mac OS X, and Linux. This means that no matter what type of device your users have access to they will be able to experience your application or website without any issues or delays due to incompatibility between platforms. There are also a growing number of web integrations in the works thanks to the Pluto.jl team which should significantly widen the audience of people who can use Julia.
Check out Julia’s download page for a full picture on the supported platforms: https://julialang.org/downloads/
You might also be interested to know that there is active work in the Julia ecosystem to support the development of generic executables which could make Julia even more flexible. At JuliaCon 2023, Jeff Bezanson talked about this work and shared it is a focus for the ecosystem.
One of the biggest reasons why startups are turning to Julia is because it offers unparalleled speed and efficiency when compared with other languages. This makes it ideal for businesses that need to process large amounts of data quickly and accurately. To put it simply, Julia can do more in less time than many other programming languages, making it a great choice for businesses that need a quick turnaround on their data-driven projects.
In a case study published to the JuliaHub website on how Julia is used by Pfizer, they say:
Pfizer used Julia to accelerate several models:
Steady state calculations of a cardiac model went from nearly a day to just 40 minutes — an improvement of 26x. With multithreading, the total simulation time was reduced to just 9 minutes — an improvement of 115x.
You might also be interested in learning more about Julia’s speed characteristics and how to perform your own benchmarks. If so, check out this article:
Another reason why startups are investing in Julia is because it is incredibly versatile. It can be used for everything from statistical analysis and machine learning algorithms to web applications and image processing programs. This wide range of capabilities makes Julia an attractive choice for businesses that need a programming language that can handle any type of project they might have.
Most applications of Julia are in the Scientific computing ecosystem, but you can even do workflows like web development as Genie Cloud shows in this video:
Finally, startups love Julia because it is easy to use and learn. While some programming languages require extensive training before you can even write your first line of code, Julia makes getting started much easier by offering intuitive syntax and an interactive development environment (IDE) with helpful tools like autocomplete in VS Code and debugger support. This makes it possible for new developers to ramp up quickly without having to invest too much time in learning the language itself.
The ease of use factor is very real in Julia, if you want to learn more, head to this article where we go into the details of why Julia is a great language for new programmers:
But it is not all sunshine and rainbows, there are some concepts in Julia that are a bit tricky to understand, so I broke them down in another article:
In conclusion, the popularity of Julia among startups speaks volumes about its capabilities as a programming language. With its speed, versatility, and ease-of-use, there’s no wonder why so many businesses are choosing this powerful language as their go-to tool for developing software solutions. If you’re looking for a modern language that can help your business stay ahead in today’s competitive landscape, then look no further than the remarkable power of Julia Programming Language!
Side note, thank you for reading this article. I am thrilled to share that my co-author and I are working on a new book: “Julia Crash Course” which is open for digital pre-orders today:
P.S. If your company is using Julia for something cool, I would love to hear about it, please get in touch!
