Bengaluru, India – Forbes Asia has published a major feature on Julia Computing and Julia.
The article is titled “How a New Programming Language Created by Four Scientists Is Now Used by the World’s Biggest Companies” by Suparna Dutt D’Cunha. It describes the geneses of Julia and Julia Computing and how Julia is being used today.
For example, Julia users, partners and firms hiring Julia programmers include Amazon, Apple, BlackRock, Capital One, Citibank, Comcast, Disney, Facebook, Ford, Google, Grindr, IBM, Intel, KPMG, Microsoft, NASA, Oracle, PwC and Uber.
So far, the article has more than 60 thousand page views and that number is still climbing.
As Stefan Karpinski, Julia Computing CTO for Open Source, explains, “Julia empowers data scientists, physicists, quantitative finance traders and robot designers to solve problems without having to become computer programmers or hire computer programmers to translate their functions into computer code.”
About Julia and Julia Computing
Julia is the fastest modern high performance open source computing language for data, analytics, algorithmic trading, machine learning and artificial intelligence. Julia combines the functionality and ease of use of Python, R, Matlab, SAS and Stata with the speed of C++ and Java. Julia delivers dramatic improvements in simplicity, speed, capacity and productivity. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. With more than 1.2 million downloads and +161% annual growth, Julia is one of the top programming languages developed on GitHub and adoption is growing rapidly in finance, insurance, energy, robotics, genomics, aerospace and many other fields.
Julia users, partners and employers hiring Julia programmers in 2017 include Amazon, Apple, BlackRock, Capital One, Citibank, Comcast, Disney, Facebook, Ford, Google, Grindr, IBM, Intel, KPMG, Microsoft, NASA, Oracle, PwC and Uber.
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Julia is lightning fast. Julia is being used in production today and has generated speed improvements up to 1,000x for insurance model estimation and parallel supercomputing astronomical image analysis.
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Julia provides unlimited scalability. Julia applications can be deployed on large clusters with a click of a button and can run parallel and distributed computing quickly and easily on tens of thousands of nodes.
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Julia is easy to learn. Julia’s flexible syntax is familiar and comfortable for users of Python, R and Matlab.
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Julia integrates well with existing code and platforms. Users of C, C++, Python, R and other languages can easily integrate their existing code into Julia.
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Elegant code. Julia was built from the ground up for mathematical, scientific and statistical computing. It has advanced libraries that make programming simple and fast and dramatically reduce the number of lines of code required – in some cases, by 90% or more.
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Julia solves the two language problem. Because Julia combines the ease of use and familiar syntax of Python, R and Matlab with the speed of C, C++ or Java, programmers no longer need to estimate models in one language and reproduce them in a faster production language. This saves time and reduces error and cost.
Julia Computing was founded in 2015 by the creators of the open source Julia language to develop products and provide support for businesses and researchers who use Julia.
