Julia in the News
Julia is an open-source language for high-performance technical computing and data science.
22 JUN 2017 | J Vignesh | Economic Times
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.
Julia Computing provides a high performance open source computing language for data, analytics, algorithmic trading, machine learning and artificial intelligence.
20 JUN 2017 | FinSMEs Staff | FinSMEs
Julia Computing builds professional software tools to make it easier for organizations, especially in the finance world, to make use of the Julia language, which is particularly good for in-demand tasks like data analytics and machine learning. Asset manager BlackRock and large British insurer Aviva are both Julia Computing customers, for example.
Julia Computing has a chance to redefine the way mathematics and science are practiced. The way Red Hat makes Linux approachable to enterprises, Julia Computing does for the Julia programming language.
19 JUN 2017 | David Frankel | Hacker Noon
Viral Shah, co-founder of Julia Computing and a co-creator of the Julia programming language, said companies need to decide the level of cyber risks assessing their threat landscapes. Shah said data protection is a three-step process that requires companies to safeguard their hardware with sufficient security protocols,monitor data access and make sure it's encrypted.
19 MAY 2017 | Anand J | Times of India
‘Why we created Julia’ ... went viral on Reddit and Hacker News, getting more than 200,000 hits in a day. It was a big tipping point.
Julia now has 250,000 users around the world and is doubling every nine months.
30 APR 2017 | Akram Mohammed | New Indian Express
This new language’s popularity is largely due to three things: support, community, and speed.
Julia Computing is working on an AI-powered software capable of diagnosing diabetic retinopathy, a degenerative condition that affects eyesight. The developers have trained a neural network using a huge dataset of images showing infected eyes and those free from the condition. In this way, the technology could theoretically be applied in a patient’s home, using a high quality smartphone camera. This way, the patient can self-diagnose for the condition before visiting a doctor, and even track the advancement of his condition.
Predictive analytics and machine learning are the future of tech, so I would focus on math, statistics, and behavioral psychology, says Jill Witty, VP of Talent at Entelo. Regarding programming languages and back-end tech I would emphasize R, Python, Java, JavaScript, Julia, Scala, and Hadoop, among others.
05 JUN 2017 | Paul Heltzel | CIO.com
Viral Shah, CEO and co-founder of Julia Computing says the industry focus is robustness but academia believes in experimentation.
The TIOBE Index expects that in 2017, the favored candidates for programming language of the year will include Apple's Swift, Julia, the Microsoft-created TypeScript, and the ever-popular C++.
10 JAN 2017 | Matt Weinberger | Business Insider
Will Julia turn into one of the popular languages for machine learning and data science? Time will tell.
13 FEB 2017 | Jean-Francois Puget | Silicon Republic
Julia has specific features built into the core language that make it particularly suitable for working with the real-time streams of Big Data industry wants to leverage these days, such as parallelization and in-database analytics. The fact that code written in Julia executes very quickly adds to its suitability here.
Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. Julia’s Base library, largely written in Julia itself, also integrates mature, best-of-breed open source C and Fortran libraries for linear algebra, random number generation, signal processing, and string processing.
Julia is a fast-maturing programming language developed to be simple to learn, highly dynamic, operational at the speed of C, and ranging in use from general programming to highly quantitative uses such as scientific computing, machine learning, data mining, large-scale linear algebra, and distributed and parallel computing.
What I like about Julia is that it is very easy to use, and despite being as easy to use as Python, you still have a lot of low level control.
04 FEB 2016 | Werner Schuster | Info Q
[Julia] provides an early glimpse into what programming languages might look like in the not too distant future.
The benefits of using Julia over other languages for scientific work include: its low barrier to entry for scientists and mathematicians, its flexibility and high performance (comparable to C), its graphics and visualization capabilities, and its ability to handle large computational problems efficiently.
Julia is a big deal. It’s a free alternative to proprietary tools for doing data science … and it’s more contemporary than open-source languages R and Python.
A number of [corporations] across the world are now finding real-world use for Julia, which can be deployed in … areas such as data science and recommendation engines, especially in sectors such as ecommerce, finance and engineering.
Overall, Julia is a welcome addition [to the High Performance Computing (HPC)] community. …The future looks bright for Julia. New and existing HPC coders will appreciate a dirt-simple on-ramp to the HPC superhighway.
26 JAN 2016 | Douglas Eadline | THE NEXT PLATFORM
Delivering Hadoop style parallelism, ... [Julia] is destined to make a major impact.
01 JAN 2016 | Mark Trego | CODING DOJO
Julia should be on the radar of everyone from traders and operations executives to IT managers, developers and data scientists and really anyone who wants to expand their job options as electronic trading takes over and the industry as a while becomes more technology-centric.
Julia is a really well-thought-out language. …it has a rigorous but infinitely flexible type system …. When these features are combined with the built-in just-in-time (JIT) compiler, they let code … run as fast as C or Fortran. But the real killer is that you can do this with code as concise and expressive as Python. … So why not make your next language Julia? It might even be the last one you need to learn.
31 MAR 2016 | Sam | OCEANOGRAPHER’S CHOICE
Julia provides the productivity and performance equivalent to five major programming languages including R, Python, Matlab, C, and Fortran. It further provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive library of fast mathematical functions.
Julia, an open source computing language, caters to data, analytics, algorithmic trading, machine learning and artificial intelligence.
22 JUN 2017 | Vijayakumar Pitchiah | VCCircle
Julia's advantages over other languages include speed improvements, unlimited scalability, and easy integration with existing code platforms.
Julia delivers dramatic improvements in simplicity, speed, capacity, and productivity to solve massive computational problems quickly and accurately. It is the preferred language for big data and analytics. It is an open source project with a diverse community of almost 500 contributors around the world.
20 JUN 2017 | News Center Staff | News Center
Programming is an important element of the master’s. The curriculum incorporates C++, as well as Python and R. In a couple of years’ time, the university may add a new programming language: Julia. “It’s more recent, it’s extremely fast and convenient to program with, and its use is expanding,” says Jacquier.
19 JUN 2017 | RISK.NET STAFF | RISK.NET
Intel India is collaborating with Hewlett Packard Enterprise, Wipro, Julia Computing, and Calligo Technologies, by enabling them with AI solutions based Intel architecture.
Julia has built a strong following. It has a number of Hadoop style features, which makes it a very useful programming language for developers working on big data projects.
16 JUN 2017 | Annie Qureshi | Sustainable Business Forum
Julia parallel computing tools ... made these speedups possible.
13 MAY 2017 | Abhi Gupta, et al | Global Economic Intersect
All of this makes Julia a one-stop shop for the various stages of a complex machine-learning project.
The team behind the Julia programming language have now ported the language to the Raspberry Pi hardware and have added support for GPIO, the Sense HAT and Minecraft.
15 MAR 2017 | Julian Horsey | Geeky Gadgets
TIOBE expects next year's top candidates to be Apple's Swift language, Julia, and the Microsoft-maintained TypeScript.
Julia is a high-performance language for processing and visualizing data in cloud environments, Julia is also open source. It was designed with parallelism in mind and includes key elements for distributed computation.
Julia Computing focuses on building products at the intersection of machine-learning and big data to solve problems in areas such as algorithmic trading, self-driving vehicles, astrophysics, drug discovery and augmented reality.
This programming language compiles straight to machine code as it runs, it seems to be a valid alternative to Hadoop and it might follow in the footsteps of C speed wise.
11 NOV 2016 | Gabriela Montroc | Jaxenter
Julia, a high-level dynamic language for technical programming, is gaining a foothold among developers. For the first time, the language has cracked the top 50 in this month's Tiobe Index of language popularity, rising to 47th place.
Julia is a free, open-source computer programming language that is gradually becoming a popular alternative to more established languages such as MATLAB and Python. Envisioned as a way to avoid the difficulties of using slower, older languages for today’s more advanced analytical applications, without compromising on ease of use, Julia has found fans around the world, drawing a sizable community of users since its launch in 2012.
Julia is poised to become one of the leading tools deployed by developers and programmers at banks, hedge funds, regulators and vendors.
Julia is ... faster at its core than Python. It also features a growing list of packages, covering not just math and science applications, but also other functionalities associated with Python, like connectivity to data sources on cloud providers.
27 JUN 2016 | Serdar Yegulalp | InfoWorld
Data hackers get giddy when talking about [Julia’s] potential to oust R and Python from their thrones. Julia is a high-level, insanely fast and expressive language. It’s faster than R and potentially even more scaleable than Python, and fairly easy to learn.
14 MAY 2014 | Anna Nicolaou | FAST COMPANY
Julia boasts performance as fast as that of languages like C or Fortran, and is still simple to learn. … We tested our code and found that the model estimation is about ten times faster with Julia than before, a very large improvement.
03 DEC 2015 | Smith | FEDERAL RESERVE BANK OF NY
Julia is fast, … can call C directly without a wrapper, integrates top tier open source C and Fortran code into its Base library, and can easily call Python as well. Julia is built for parallel and cloud computing, and has particular interest from the analytics and scientific computing communities. According to KDnuggets' most recent analytics software poll, Julia placed 8th on the list of most used programming languages.
AUG 2016 | Matthew Mayo | KDnuggets
[I]t’s notable that Julia, a high-level programming language built expressly for use in technical computing, has entered TIOBE’s list …. In industries that prize efficiency, such as finance, Julia has enjoyed rapid adoption by tech professionals and data scientists. In banking and trading, algorithmic traders and quants now rely on Julia because it allows them to push code as quickly as possible to market, without needing to rewrite.
[Julia has] generated an excited buzz in scientific computing circles. Julia may be the first language since Fortran created specifically with scientific number crunching in mind. Julia allows expressive programming using sophisticated abstractions while attaining C … speed in many benchmarks. …Julia has powerful concurrency and networked programming facilities; it can interface seamlessly with Fortran and C library routines … and it’s able to act as shell-like glue code. Julia can be as simple and direct to program in as Python while offering an order of magnitude increase in speed.
07 MAY 2014 | Lee Phillips | Ars Technica
Big-data languages, such as Julia, Python, R and Scala … are purpose-built for handling large amounts of numeric data, with stables of packages that can be tapped for quick big-data analytic prototyping.
03 JUN 2016 | Nicholas Diakopoulos | IEEE SPECTRUM
Julia Computing focuses on building products at the intersection of machine-learning and big data to solve problems in areas such as algorithmic trading, self-driving vehicles, astrophysics, drug discovery and augmented reality.
20 JAN 2017 | J Vignesh et al | Economic Times
The new code in Julia is easier to read than the R code because Julia has fewer syntactic quirks than R. More importantly, the Julia code runs much faster than the R code without any real effort put into speed optimization. For the sample text I tried to decipher, the Julia code completes 50,000 iterations of the sampler in 51 seconds, while the R code completes the same 50,000 iterations in 67 minutes — making the R code more than 75 slower than the Julia code.
31 MAR 2012 | John Myles White | John Myles White
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