In this episode of The Programming Languages Podcast, Lucas and Luna dive into Julia — the high-performance language that's quietly reshaping scientific computing, data science, and machine learning. They explore why Julia's just-in-time compilation and multiple dispatch make it a compelling alternative to Python for numerical work, and discuss how the Pumas project is using Julia for pharmaceutical modeling at scale. They also touch on Julia's growing package ecosystem and its adoption in fields like climate science and quantitative finance. If you're a developer curious about where scientific computing is heading, this episode offers a concrete look at one language leading the charge.

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