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

By JuliaHub | Feb 08, 2017

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.



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