We wanted to thank all Julia users and well wishers for the support and for being part of the Julia Community, and to give an update on some exciting developments for May 2018:
“The initial drive behind Julia was the desire for a programming language that combined elements of the high-level functionality of MATLAB and R with the speed of C or Ruby - as [Julia co-creator Stefan] Karpinski put it, ‘the best of all worlds.’ …they wanted ‘a Goldilocks programming language - one that was high level and low level at the same time, depending on how you used it,’ said Karpinski. The Goldilocks ideal gave way to the Julia project: an open-source, dynamic programming language…”
“Julia is another great language with an open and active community. They are currently investing in machine learning techniques, and even have good interoperability with Python APIs. The Julia community shares many common values as with our project, which they published in a very like-minded blog post after our project was well underway. We are not experts in Julia, but since its compilation approach is based on type specialization, it may have enough of a representation and infrastructure to host the Graph Program Extraction techniques we rely on.”
Inside Venture Capital: Interview with Julia Computing’s Viral Shah (Note: Subscription Required)
“The inspiration for Julia Computing is the demand for Julia,” says Viral Shah.
“Rajshekar Behar, marketing leader at Julia Computing – a rapidly rising startup specializing in AI solutions – says: ‘I believe we keep mixing HPC with AI. AI is an application that needs high performance computing. When you start solving a problem, you reach a point where you want to delegate the decision making to a system, because you think it’s going to take better decisions. And that’s when you implement AI with HPC,’ he explains.”
“HPC is still committed to its lower level tools and that will remain the case with domain scientists dabbling in Python until it fails to scale. This seems to clear the way for either Julia or Chapel.”
“‘I do think that, at a business level, as well as at a national level, we have a lot of catching up to do…’ says Viral Shah, co-founder of Julia Computing. He adds that Indian firms today have a lot of data but the skill in asking questions on what can be done with data for effectively building AI models is missing.”
“Rajshekar Behar, marketing leader at Julia Computing, a rapidly rising startup specializing in AI solutions, believes that investing in learning holds the key to AI growth. ‘The major barrier I see is that the gap between haves and have-nots keeps increasing. One way to tackle this problem is to invest in the infrastructure of learning. The skillset required for AI is not rocket science, so colleges need to include AI in their curriculum,’ he adds.”
“Also in this month’s index, Kotlin and Julia both entered the top 40… Julia, in 37th place … is used in scientific computing and [the] burgeoning field of machine learning.”
“The RStudio community plans to provide support to other languages such as Julia and Haskell.”
“Apache Zeppelin joins a growing list of data science notebooks that include Databricks Cloud, Jupyter (the successor to the iPython Notebook), R Markdown, Spark Notebook and others. Backends to multiple languages include Python, Julia, Scala, SQL and others.”
We are introducing several new online, instructor-led, and video training options for Julia. For more information on online and instructor-led classes, please contact [email protected]. Training videos are also available online:
JuliaCon is coming to University College London Aug 7-11, 2018.
Bangalore: Artificial Intelligence and Machine Learning in Julia with Julia Computing and MSRIT May 2-4
Boston: Mulithreaded Scheduling with Kiran Pamnany and Cassette.jl with Jarrett Revels and Julia Computing at MIT Stata Center May 15
London: What Every Quant Should Know about Technical Computing with Julia Computing and the CQF Institute May 15
Oaxaca: Workshop in Statistical Methods on Distributed Computing with Julia Computing May 20-25
Bangalore: Jump-Start to Exemplary Skills in AI Using Julia & Python Language Jun 9
Freiburg: IEEE Statistical Signal Processing Workshop Jun 10-13
Bangalore: Artificial Intelligence and Machine Learning in Julia with Julia Computing at Infosys Jun 12-15
Bordeaux: JuMP-dev Workshop at Institut de Mathématiques de Bordeaux, University of Bordeaux Jun 27-29
London: JuliaCon 2018 at University College London Aug 7-11
Bangalore: Jump-Start to Exemplary Skills in AI Using Julia & Python Language Aug 11
Chicago: Intro to Julia Tutorial with Julia Computing and Illinois Institute of Technology Association for Women in Mathematics at the Illinois Institute of Technology Mar 6
Chicago: Intro to Julia Tutorial with Julia Computing and Harold Washington College STEM Club Mar 8
Montreal: Plots.jl and Intro to Package Development Mar 8
San Jose: Cataloging the Visible Universe through Bayesian Inference at Petascale in Julia at Strata Data Conference Mar 9
Chicago: Intro to Julia Tutorial with Julia Computing and University of Chicago Association for Computing Machinery Council on Women in Computing at the University of Chicago Mar 9
Cleveland: Let’s Challenge Numerai Competition Together Mar 10
Washington DC: ARPA-E Energy Innovation Summit with Julia Computing Mar 13-15
Washington DC: Machine Learning and Programming Languages with Julia Computing Mar 14
Exeter: Go, Julia and Expanding Your Toolbox Mar 14
Warsaw: Spotkanie na Konferencji Supercomputing Frontiers Europe 2018 Mar 15
London: Introduction to Julia Mar 20
San Francisco: Introduction to Julia for Data Analytics with Julia Computing at University of San Francisco School of Management Mar 23
San Jose: NVIDIA GPU Technology Conference Mar 26-29
Los Angeles: PyData SoCal Meetup Mar 29
Global: Intro to Julia with Julia Computing Apr 6
Global: Introducción a Julia en Español Apr 7
Tucson: HPC User Forum Apr 16-18
San Sebastian: International Spring School on High Performance Computing with Julia Computing Apr 23-27
Bangalore: Introduction to Julia with Julia Computing and Lucida Technologies Apr 25
Bangalore: Artificial Intelligence and Machine Learning in Julia with Julia Computing Apr 27-29
There are 26 Julia Meetup groups worldwide with more than 5 thousand members. If there’s a Julia Meetup group in your area, we hope you will consider joining, participating and helping to organize events. If there isn’t, we hope you will consider starting one.
Do you work at or know of an institution looking to hire Julia programmers as staff, research fellows or interns? Would your employer be interested in hiring interns to work on open source packages that are useful to their business? Help us connect members of our community to great opportunities by sending us an email, and we’ll get the word out!
There are more than 200 Julia jobs currently listed on Indeed.com, including jobs at Google, Facebook, IBM, KPMG, Ernst & Young, Booz Allen Hamilton, Comcast, Zulily, National Renewable Energy Research Laboratory, Los Alamos National Laboratory, Brown, Princeton, Columbia, Notre Dame, MIT, University of Chicago and many more.
Penn State University’s Department of Astronomy and Astrophysics Center for Exoplanets and Habitable Worlds (CEHW) is looking to hire a Postdoc Researcher and Assistant Research Professor with Julia experience.
Please contact us if you wish to:
Julia is the fastest high performance open source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and many other domains. Julia solves the two language problem by combining the ease of use of Python and R with the speed of C++. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. For example, Julia has run at petascale on 650,000 cores with 1.3 million threads to analyze over 56 terabytes of data using Cori, the world’s sixth-largest supercomputer. With more than 1.8 million downloads and +101% annual growth, Julia is one of the top programming languages developed on GitHub. Julia adoption is growing rapidly in finance, insurance, machine learning, energy, robotics, genomics, aerospace, medicine and many other fields.
Julia Computing was founded in 2015 by all the creators of Julia to develop products and provide professional services to businesses and researchers using Julia. Julia Computing offers the following products:
Julia users, partners and employers hiring Julia programmers in 2018 include Amazon, Apple, BlackRock, Booz Allen Hamilton, Capital One, Comcast, Disney, Ernst & Young, Facebook, Ford, Google, IBM, Intel, KPMG, Microsoft, NASA, Oracle, PwC, Uber, and many more.