A programming language for scientific machine learning and differentiable programming

The Data Exchange Podcast: Viral Shah on the evolution and maturation of Julia.

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In this episode of the Data Exchange I speak with Viral Shah, co-founder and CEO, Julia Computing. Along with his Julia language co-creators, Viral was awarded the 2019 Wilkinson prize, for outstanding contributions in the field of numerical software. I first tweeted about Julia at the beginning of March 2012  after seeing Jeff Bezanson give a talk in Stanford. I’ve dabbled with it here and there, but have never used it for a major project. Over the past few years, Julia continued to add packages at a steady pace and the package manager is really quite impressive and solid.  We spent much of the podcast discussing the state of Julia, Julia 1.5, the Julia ecosystem and community.

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If your application requires complex computations and you have strict performance requirements, Julia is definitely a solid candidate. With that said,  the rise of deep learning has made Python the dominant language for ML as many of the popular libraries targeted Python from the get-go.

We also discussed Viral’s 2016 book –  Rebooting India: Realizing a Billion Aspirations – which he co-wrote with Nandan Nilekani, co-founder of Infosys Technologies.

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[Image: Mandel zoom 12 satellite spirally wheel with julia islands from Wikimedia]