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💡Are you Interested in open source sustainably? Dr. Chris Rackauckas shares JuliaSim's approach to: ✔️ Scientific computing at scale ✔️ Community-first development ✔️ Industry partnerships ✔️ Join us on January 16, 12 pm ET! buff.ly/3BvoTj4 #Julia #OpenSource

🌐 Building bridges between #OpenSource & industry. Don't miss Dr. Chris Rackauckas sharing insights on scientific ML development, community sustainability, and product evolution. Hosted by OpenTeams Jan 16, 12pm ET buff.ly/3WfcbMp🚀

Julia is on a remarkable growth trajectory! 🚀 Over the past 5 years: - Discourse views increased by +494% (136M+) - GitHub stars grew by +412% (511K+) - Published citations rose by +391% (8K+) - Registered packages expanded by +322% (11K+) These numbers reflect Julia's impact

How do you build products that support open source communities? In this non-technical talk with #OpenTeams I discuss how the MIT CSAIL Julia Lab, @PumasAI, and JuliaHub have all been essential pillars of the #julialang #opensource community. youtube.com/watch?v=kuzwUF…

Using higher order automatic differentiation to improve stiff ODE solvers? Using a third order Newton-like method (Halley's) inside the #sciml #julialang ODE solvers with Taylor-mode AD, ~25% faster. arxiv.org/abs/2501.16895

💡 Great insight from Dr. Chris Rackauckas: Sometimes the best companies emerge from identifying gaps in scientific software. See how JuliaSim went from concept to reality in our latest OSA community talk: buff.ly/42qLTe8 #Innovation #ScienceTech

Law of controls: write C code for real-time embedded hardware. You can't use #python or #rstats etc. for that, right? With #julialang v1.12, we demonstrate it's possible to ahead of time compile to small binaries for use in controls applications. #sciml arxiv.org/abs/2502.01128

🔗 Where deep learning meets recommendation systems - Dr. Chris Rackauckas explores unexpected connections in open source development in a recent OSA event. Watch how these insights could transform your next project: buff.ly/42qLTe8 #MachineLearning #OpenSource

New blog post: How chaotic is chaos? How some AI for Science / SciML papers are overstating accuracy claims. stochasticlifestyle.com/how-chaotic-is… #julialang #sciml #chaos #ergodic #ai4science

New blog post: Machine learning with hard constraints: Neural Differential-Algebraic Equations (DAEs) as a general formalism. stochasticlifestyle.com/machine-learni… #sciml #ai4science #hardconstraints #neuralnetworks #dae #acausal #modelingtoolkit #julialang #modelica

Artistic rendition of using #julialang on models with only 3 ODEs youtube.com/watch?v=cHl_gs…

Today JuliaHub is announcing Dyad, a new declarative language for modeling physical systems. It's the culmination of over a year of product development and a decade of work on #JuliaLang's SciML Scientific Machine Learning Software Org ecosystem