Julia is Causing Quite a Stir with Code Modernization in the Tech Industry

Julia is on its way to excellence through code modernization.

The present tech industry is in dire need of a programming language that provides the best of C or C++ and the usability of Python. All of these capabilities are at the heart of what the open-source Julia language project set out to do over a decade ago. When Julia was conceived in 2009 at MIT, the goal was to solve a problem that still exists: the need to use two (or more) languages, one for high performance (C or C++) and another that made programming complex systems a more pleasant experience (the Python example). While using both could get the job done, there is inherent friction between those interfaces and processes. In addition to this basic mismatch, many of the codes in high-value science and engineering are the product of decades of building. They are inherently messy and rooted in codes that were state of the art in the 1980s, particularly in modeling and simulation.

The Origin of Julia

Despite the clear call of support from MIT, it wasn't until 2012 that Julia became an open-source language project and even then, it was still a relatively small effort, not producing a 1.0 release until late 2018. There were some bumps in the road, learning to live as an open-source effort with bug fixes every month requiring early users to continually adjust, but things have been stable since then, and at exactly the right time. With the language as a springboard, one of the long-time committers to the Julia language, Keno Fischer, started to look around at the real-world problems Julia could begin solving, not just as a standalone language but as a supported platform, a self-contained ecosystem. After nearly a decade working on Julia's low-level compiler and other nitty-gritty features, Fischer, along with two other long-term Julia creators, co-founded Julia Computing. The goal was to put Julia to the test, not just as a language but as a more streamlined way to code for pharmaceutical, financial, HPC, energy, and other segments.

Latest Use of Julia

In the last year or two, these efforts have paid off. Julia Computing has aided Pfizer in simulating new pharmaceuticals, AstraZeneca with AI-based toxicity prediction, European insurance giant Aviva with its compliance issues, energy provider Fugro Roames with an AI-based grid network failure prediction system, the FAA with its airborne collision prevent program, Cisco with ML-based network security, and several national labs and academic institutions with various research programs. Julia Computing made waves this month as well with a DARPA grant to bring semiconductor codes up to date for more efficient, modern simulation codes. That DARPA work highlights why we'll be hearing more about Julia, the language, and the company that spun off.

Recent News of Funding

Julia Computing raised $24 million in a funding round led by venture capital firm Dorilton Ventures and said Bob Muglia, former chief of software provider Snowflake Inc, would join the computing solutions company's board. The funding round also included participation from Menlo Ventures, General Catalyst, and HighSage Ventures, Julia Computing said in a statement to Reuters on Monday. The company was founded in 2015 by the creators of the Julia programming language, which was originally developed at the Massachusetts Institute of Technology (MIT) and introduced to the public in 2012. The language is used in artificial intelligence, data science, machine learning, modeling, and simulation. More than 10,000 companies across the globe use the language, including AstraZeneca PLC, BlackRock, and Microsoft Corp, Julia Computing said. NASA, the Federal Aviation Administration (FAA), and the Federal Reserve Bank of New York also use Julia.