Julia Used to Win Industrial Internet of Things (IIoT) Hackathon

By: Julia Computing, Inc.

Re-posted from: http://juliacomputing.com/press/2017/02/08/iiot-competition.html

Graz, Austria – Julia Computing is pleased to congratulate Tangent
Works on winning the Industrial Internet of Things (IIoT) hackathon
using Julia. The IIoT hackathon was centered on big data and machine
learning analysis and was organized by Andritz and Pioneers Discover in
Graz, Austria from Jan 23-25, 2017.

Tangent Works competed with several European startups to win first
place. Competitors were required to solve 5 different tasks related to
IIoT, largely focused on optimization and predictive maintenance.

According to Milan Garbiar, Managing Director at Tangent Works, “We
relied heavily on Julia during the hackathon. We were the only
competitor using Julia. This, and the fact that we were able to use our
product, which is written in Julia, gave us a considerable advantage
compared with our competitors who relied largely on Python and R.”

Viral Shah, Julia Computing CEO said, “This is another great example of
the power of Julia. Because of Julia’s intuitive syntax, faster speed,
simpler coding and greater capacity for big data, Julia is the best
choice for optimization when speed and simplicity matter most.”

About Julia Computing and Julia

Julia Computing (JuliaComputing.com) was
founded in 2015 by the co-creators of the Julia language to provide
support to businesses and researchers who use Julia.

Julia is the fastest modern high performance open source computing
language for data and analytics. It combines the functionality and ease
of use of Python, R, Matlab, SAS and Stata with the speed of Java and
C++. Julia delivers dramatic improvements in simplicity, speed, capacity
and productivity.

  1. Julia is lightning fast. Julia provides speed improvements up to
    1,000x for insurance model estimation, 225x for parallel
    supercomputing image analysis and 11x for macroeconomic modeling.

  2. Julia is easy to learn. Julia’s flexible syntax is familiar and
    comfortable for users of Python, R and Matlab.

  3. Julia integrates well with existing code and platforms. Users of
    Python, R, Matlab and other languages can easily integrate their
    existing code into Julia.

  4. Elegant code. Julia was built from the ground up for
    mathematical, scientific and statistical computing, and has advanced
    libraries that make coding simple and fast, and dramatically reduce
    the number of lines of code required – in some cases, by 90%
    or more.

  5. 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.

Employers looking to hire Julia programmers in 2017 include: Google,
Apple, Amazon, Facebook, IBM, BlackRock, Capital One,
PricewaterhouseCoopers, Ford, Oracle, Comcast, Massachusetts General
Hospital, NaviHealth, Harvard University, Columbia University, Farmers
Insurance, Pilot Flying J, Los Alamos National Laboratory, Oak Ridge
National Laboratory and the National Renewable Energy Laboratory.

Julia users and partners include: Amazon, IBM, Intel, Microsoft,
DARPA, Lawrence Berkeley National Laboratory, National Energy Research
Scientific Computing Center (NERSC), Federal Aviation Administration
(FAA), MIT Lincoln Labs, Moore Foundation, Nobel Laureate Thomas J.
Sargent, Federal Reserve Bank of New York (FRBNY), Capital One,
Brazilian National Development Bank (BNDES), BlackRock, Conning, Berkery
Noyes, BestX, Path BioAnalytics, Invenia, AOT Energy, AlgoCircle,
Trinity Health, Gambit, Augmedics, Tangent Works, Voxel8, UC Berkeley
Autonomous Race Car (BARC) and many of the world’s largest investment
banks, asset managers, fund managers, foreign exchange analysts,
insurers, hedge funds and regulators.

Universities and institutes using Julia include: MIT, Caltech,
Stanford, UC Berkeley, Harvard, Columbia, NYU, Oxford, NUS, UCL, Nantes,
Alan Turing Institute, University of Chicago, Cornell, Max Planck
Institute, Australian National University, University of Warwick,
University of Colorado, Queen Mary University of London, London
Institute of Cancer Research, UC Irvine, University of Kaiserslautern.

Julia is being used to: analyze images of the universe and research
dark matter, drive parallel computing on supercomputers, diagnose
medical conditions, provide surgeons with real-time imagery using
augmented reality, analyze cancer genomes, manage 3D printers, pilot
self-driving racecars, build drones, improve air safety, manage the
electric grid, provide analytics for foreign exchange trading, energy
trading, insurance, regulatory compliance, macroeconomic modeling,
sports analytics, manufacturing and much, much more.