The #Julialang Dispatch podcast wrapped said we were in the top 20% of videos on on Spotify this year! Also it was a heavily marathoned show, meaning "Fans listened to you for longer than 91% of shows" Looks like everyone is staying to the end 😘.

Scientific machine learning (#SciML) is not just about adding scientific information to machine learning, but it's also about making machine learning accessible to heterogeneous data. youtube.com/shorts/jop2S...

New livestream, #Dyad Modeling Live! In this stream we built up a thermal model of a room using #AgenticAI and added a heat pump with different control strategies and analyzed the power efficiency. Join the fun live next week! #julialang #sciml youtube.com/live/I542x6g...

How to properly cook your turkey, using agentic AI and #dyad #julialang! Happy Thanksgiving from JuliaHub, hope we can help you with acausal modeling to change your family's holiday! youtube.com/shorts/qv6Qv...

A lot of people think JIT compilers, or the compilation process in general, magically makes programming languages faster. "Just add a compiler", nope that's voodoo. So why are "traditional compiled languages" like C and Fortran faster? #JuliaLang youtube.com/shorts/Z1_vZ...

ANSYS /Synopsys, one of the largest simulation companies in the world, is partnering with @JuliaHub_Inc in order to bring #Dyad, #Julialang, and #SciML to next level of adoption. We have many things planned. This is how research becomes reality. www.prnewswire.com/news-release...

#SciML fact of the day: automatic differentiation fails to give the correct derivative on a lot of very simple functions 😱 😱 😱 . #julialang #automaticdifferentiation youtube.com/shorts/KTguZ...

Can Agentic AI turn single purpose code into reusable modular code? Dyad's specialized AI can! Watch our latest video on AI-assisted model restructuring and physics enhancement: www.youtube.com/watch?v=0RdA... #ModelingAndSimulation #AIAgent #JuliaLang #SciML #Dyad #SystemsEngineering #Modelica

Check out the latest #Julialang Dispatch Podcast! This episode goes over the changes to the Julia language, its standard libraries, and the main changes in the package ecosystem (#sciml, JuMP, etc.) that occurred over the summer. Most posts coming soon as well! www.youtube.com/watch?v=q3_W...

Watch Dyad's AI agent build a complete thermal model from just an image! Picture -> validated DAEs in minutes. Features: Auto parameter generation, model optimization, custom animations. All with production-ready Julia code. youtu.be/eKLDVCkJC1s #dyad #julialang #sciml

#Dyad #SciML tutorial! Use Dyad's graphical/textual #acausal system to build models from validated model components and transform into your #digitaltwin! #Dyad = component-based modeling tool (e.g. #Modelica, #Amesim, #Simulink) + AI/ML autocomplete! www.youtube.com/watch?v=ttQI...

What is #acausal modeling and how does it lead to better reproducibility and modularity in modeling and simulation? Check out this video which goes step-by-step into building acausal models using the RC circuit and RLC circuit www.youtube.com/watch?v=rMb4... #julialang #dyad #sciml

#LLMs make mistakes. Modeling languages like #Dyad have static analysis to compile-time check whether models are physically possible. What happens when you mix the two in an #agentic workflow? Automated construction of accurate models! www.youtube.com/watch?v=hIkb... #julialang #sciml

SciML Developer Chat Episode 1: Base Splits and Symbolics Precompilation Welcome to the first episode of the SciML Dev Chat! We discuss the latest developments in the #SciML (Scientific Machine Learning) ecosystem for #julialang! youtu.be/0yQ4aZ-ABhY

MIT Julia Lab: looking for postdoctoral researchers in #julialang open source software development, scientific machine learning (#SciML), and systems biological / pharmacological modeling (#QSP) for research in equation discovery for large stiff systems. julia.mit.edu/projects/#po...

Claude code sucks... but it's still very useful! Check out this blog post that details how Claude is deployed to solve problems in the #Julialang #SciML open source scientific computing infrastructure. stochasticlifestyle.com/claude-code-... #llm #vibecoding #physics #opensource #oss

AI-Assisted Modeling in Dyad with Cursor AI! We've just released a comprehensive demonstration showing how LLMs can dramatically accelerate dynamic system modeling workflows in Dyad. youtu.be/awwJPWIlXXM?...

It's been a thrill to host Dr Chris Rackauckas for a 2-day visit to our node at QUT. Chris presented a seminar, ran a workshop on High-Performance Scientific Modelling with Julia & SciML, & met with our researchers. Chris is VP of Modelling and Simulation at JuliaHub. @chrisrackauckas.bsky.social

Scientific Modeling Cheatsheet: #MATLAB vs #Python vs #Julialang Side-by-side comparison for: • Differential equations • Optimization • Automatic differentiation • Symbolic computing • More! Highlights ecosystem differences & best practices. sciml.github.io/Scientific_M...

New workshop materials on High-Performance Scientific Modeling with Julia & SciML: • #Julialang for scientific computing • ODEs/PDEs & numerical methods • Symbolic-numeric modeling • Biological systems (Catalyst.jl) • Parameter estimation • #SciML & UDEs github.com/SciML/Julia_...

DifferentialEquations.jl is many things, and lots of people only use a small portion of it. Check out the JuliaCon 2025 workshop: introduces many aspects of the packages that the developers feel are underutilized and under-understood! #julialang #sciml www.youtube.com/watch?v=lSGF...

Dr Chris Rackauckas will present a seminar at all three university stops: "Automating Construction of Biochemical and Physical Models with Scientific Machine Learning (SciML)" 📆Tues, 23 Sept: University of Melbourne 📆Thurs, 25 Sept: UNSW 📆Mon, 29 Sept: QUT 👉https://macsys.org/event/

MACSYS is excited to host Dr Chris Rackauckas for visits to three of our node universities. He is: 🔹VP of Modelling & Simulation - #JuliaHub 🔹Director of Scientific Research - #PumasAI 🔹Co-PI - Julia Lab at #MIT 🔹Lead developer - #SciML Open Source Software Org @chrisrackauckas.bsky.social ( 🧵1/2)

Check out the JuliaCon workshop SciML in Fluid Dynamics (CFD): Surrogates of Weather Models. Go into depth on all of the major surrogate architectures and give them a try on the weather model challenge problem! www.youtube.com/watch?v=PfRx... #julialang #juliacon #sciml

Sundials.jl v5.0: Update to SUNDIALS v7 and Improved DAE Initialization A major update that brings significant improvements to differential-algebraic equation (DAE) solving and upgrades to the latest Sundials C library sciml.ai/news/2025/09... #julialang #sciml #sundials #dae

SciML Fellowship development 2025 - JumpProcesses.jl: Introducing vr_aggregator for VariableRateJumps, GPU-enhanced SimpleTauLeaping and Extending with τ-Leap Algorithms for Jump Process Simulation #julialang #ssa #gillespie #sciml #tauleap sciml.ai/news/2025/09...

Introducing SymbolicSMT.jl for symbolic constraint solving and theorem proving! Built on Z3, test the feasibility of symbolic expressions built using Symbolics.jl. Given Constraints([x > 0, y > 0, x^2 + y^2 <= 1]), ask issatisfiable? isprovable? #julialang #symbolics #smt sciml.ai/news/2025/09...

New episode of the #julialang Dispatch podcast, featuring Jesper and Philip from Cognibotics, a Swedish robotics company that developed a statically-typed dialect of Julia designed specifically for real-time robot programming! www.youtube.com/watch?v=8wja...

Yes I'll be going all over Australia. Happy to connect with anyone while there.

MACSYS will host Dr Chris Rackauckas for visits to three of our node universities this month. He is: 🔹VP of Modelling & Simulation - #JuliaHub 🔹Director of Scientific Research - #PumasAI 🔹Co-PI - Julia Lab at #MIT 🔹Lead developer - #SciML Open Source Software Org @chrisrackauckas.bsky.social

Mixed precision and automatic GPU offloading for Newton solves and stiff ODE solvers has now landed thanks to improvements in LinearSolve.jl. Run LinearSolveAutotune.jl so that things like usage of GPUs in #julialang #sciml becomes automatic! sciml.ai/news/2025/09...

New Symbolic-Numeric algorithm which uses rational polynomial interpolation mixed with differential algebra in order to give a highly robust method for parameter estimation and solving inverse problems on ODEs. #julialang #sciml #symbolicnumeric #ode www.sciencedirect.com/science/arti...

New blog post: Implicit ODE Solvers Are Not Universally More Robust than Explicit ODE Solvers, Or Why No ODE Solver is Best Talks about how "robust" methods can be less robust in practice. Justifies hundreds of methods in #julialang #sciml www.stochasticlifestyle.com/implicit-ode...

"A Guide to Gen AI / LLM Vibecoding for Expert Programmers" A perspective on the true role of Generative AI and LLM-Based Vibe Coding for the future of development. www.stochasticlifestyle.com/a-guide-to-g... #GenerativeAI #llm #claude #chatgpt #vibecoding

LinearSolve.jl just got autotuning 🔥 The problem: picking linear solvers is hardware-dependent voodoo. Solution: automatic benchmarking that tells you EXACTLY what to use. Share the results to improve the system! Details: sciml.ai/news/2025/08/16/linearsolve_autotuning/ #julialang #sciml

What is the #julialang programming language? This is stitched from the interviews of a lot of developers telling their stories as to why they are committed to the mission of #Julia. Performance, scaling, easy, fun? www.youtube.com/watch?v=jPDC... #sciml #scientificcomputing #hpc #scaling

#Julialang Dispatch: we welcome Jacob Zelko, who takes us on a fascinating journey from his early days as a #biomedical engineering student through his work at the CDC during the COVID-19 pandemic, and into his current exploration of applied #categorytheory. www.youtube.com/watch?v=HyMp...

BLIS is a really slow BLAS lol

New paper on fitting #neuroscience models to neuroimaging and electrophysiological data! We show that the previous techniques within the field (Spectral DCM) can be greatly improved using automatic differentiation, #julialang #sciml, ModelingToolkit, and more.

How successful has the SciML Small Grants program been at getting newcomers to contribute to open source software #oss for #sciml #julialang and #ai4science? Very! * 13 total projects initiated * ~90% success rate See the blog post summary of the first year! sciml.ai/news/2025/07...

How does the mission of JuliaHub and the new Dyad modeling language interact with the #julialang open source (#OSS) community? juliahub.com/blog/the-str...

Our new manuscript shows how to extend automated model discovery and universal differential equations to chaotic systems in #neuroscience using a trick from control literature known as the Prediction Error Method (PEM)! Check out the paper at: arxiv.org/abs/2507.03631 #sciml #ai4science

Check out the extended edition of our Dyad Studio tutorial! This one really dives into detail, showing you every step of using Dyad in modeling and simulation. #julialang www.youtube.com/watch?v=5zKL...

New Julia Dispatch Podcast! Join Chris Rackauckas and Stefan Krastanov as they explore the latest developments in the Julia programming language ecosystem from the March 2025 "This Month in Julia World" newsletter. www.youtube.com/watch?v=i9pe... #julialang

In this comprehensive tutorial, we'll walk you through everything you need to know to get started with #Dyad Studio - the next-generation modeling system that seamlessly combines GUI and textual modeling. www.youtube.com/watch?v=QLlX... #julialang #acausal #modelica #sciml

@JuliaHub_Inc has released a new modeling language, Dyad, which integrates traditional physical modeling a la #modlica with scientific machine learning #sciml in a high-level and declarative form. Check out our release post! juliahub.com/blog/dyad-ma... #julialang #mbse #ai

With modeling heat pumps and dehumidifiers, we were able to show that the latest boundary value problem (#BVP) solvers in #julialang #sciml outperform the Fortran wrapped bvp_solver of SciPy and the native bvp4c/5c solvers of MATLAB. Published article here: authors.elsevier.com/c/1lHcein8Vr...

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

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

New blackbox global optimization benchmarks shows that the #julialang BlackBoxOptim.jl (BBO) outperforms the classic C-based NLopt on a wide array of difficult optimization problems. See the benchmarks for more details: docs.sciml.ai/SciMLBenchma... #optimization #machinelearning #C #python