GPT 5.6 or Claude Fable, which is better for Physical AI? We put it to test in the #Dyad AI evaluation system for generating models and tuning controllers. Our evals gave pretty definitive results, check it out! juliahub.com/blog/frontie... #AgenticAI #AI4Science #SciML #Julia

GPT-5.6 vs Claude Fable 5 for Physical AI, which performs best? - Blog | JuliaHub

We tested the latest frontier models in the Dyad agent on five modeling and simulation problems, comparing accuracy, cost, time, and work style.

juliahub.com

Real-world telemetry data and Internet of Things collide with scientific machine learning #sciml? Devices which can learn how to adapt to reality and continually improve their efficiency. #UDEs with #Dyad => better thermal efficiency. See : arxiv.org/abs/2603.15943 #julialang #AI4Science

Scientific Machine Learning-assisted Model Discovery from Telemetry Data

Calibration of dynamic models to data is an important step in building building digital twins of HVAC equipment, thermal loads and control systems. Sometimes, when a model fails to calibrate to data, ...

arxiv.org

Peer reviewed result: better languages leads to better agentic AI and LLMs. A language where if you connect things that have incompatible units you get compiler errors for the agents to quickly correct. This language of AI for Science is #Dyad. www.sciencedirect.com/science/arti...

Improving process systems engineering with specialized multi-agent large language models

Multi-agent large language models (LLMs) were evaluated for Process Systems Engineering (PSE) tasks. Two multi-agent systems (Dyad 2.1 and Claude Opus…

sciencedirect.com

Join us for a Dyad Modeling Livestream today - this time at 1pm ET / 10 am PT! Michael Tiller will joining us today to model a hybrid-EV powertrain! Tune in on YouTube and send us your thoughts in the chat! www.youtube.com/watch?v=qLfV... #sciml #julialang #dyad

Dyad AI Modeling Challenge: Modeling a Hybrid EV Powertrain

YouTube video by JuliaHub

youtube.com

Recent optimizations in SciMLSensitivity.jl are having some pretty good payoffs! Given we just 2.5x'd 2 months ago, this next change of 3.2x is putting us almost an order of magnitude ahead! See the latest autodiff benchmarks docs.sciml.ai/SciMLBenchma... #sciml #julialang

New fastest explicit non-stiff ODE solver? That's right, we now have something beating the pants off of the high order explicit RK methods! Check out the new symbolic-numeric optimized Taylor methods available in DifferentialEquations.jl! #julialang #diffeq #sciml

@juliacon.org 2026 will have a minisymposium on "Methods and Applications of Scientific Machine Learning (SciML)" hosted by @chrisrackauckas.bsky.social find out more on pretalx.com/juliacon-202... and submit your proposal through juliacon.org/2026/cfp/ #julialang #sciml

Your college professor teaches you "A-stable methods are required for stiff ODEs". But PSA, the most commonly used stiff ODE solvers (adaptive order BDF methods) are not A-stable. #sciml #numericalanalysis #diffeq www.youtube.com/shorts/hmKVQ...

The most commonly used stiff ODE solver isn't A-stable?!?!?

YouTube video by Chris Rackauckas

youtube.com

Physics-Informed Neural Surrogates for Mesh-Invariant Modeling of High-Speed Flows at #AIAA #SciTech! We built a neural surrogate that predicts aerodynamic behavior 595x faster than CFD while maintaining ~1% relative error. #sciml #Julialang #CFD #Hypersonics #AIAASciTech

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...

Scientific machine learning and heterogeneous data

YouTube video by Chris Rackauckas

youtube.com

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...

Dyad Modeling Live: Creating a Thermal Model of a Room using Agentic AI

YouTube video by JuliaHub

youtube.com

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...

How to properly cook your turkey using agentic AI and #Dyad #julialang!

YouTube video by JuliaHub

youtube.com

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...

Do (JIT) compilers make code faster? Not always, it's all about program information! #julialang

YouTube video by Chris Rackauckas

youtube.com

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...

JuliaHub Partners with Synopsys to Power SciML-Based Digital Twins

/PRNewswire/ -- JuliaHub, a leader in AI-native simulation and modeling, today announced a strategic partnership with Synopsys (NASDAQ: SNPS) to integrate...

prnewswire.com

#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...

Automatic differentiation is incorrect on very simple functions??? 😱 😱 😱

YouTube video by Chris Rackauckas

youtube.com

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

Dyad Agentic Workflows: Generating Hierarchical Models and Increasing Physical Fidelity

YouTube video by JuliaHub

youtube.com

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...

This Month in Julia World - August 2025 | JuliaCon Recap & Community Updates

YouTube video by Julia Dispatch

youtube.com

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

Generating a Coffee Cup Thermal Model from a Schematic

YouTube video by JuliaHub

youtu.be

#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

Acausal vs Causal Modeling Explained with Dyad

YouTube video by JuliaHub

youtube.com

#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

Agentic modeling of a friction brake with Dyad, LLMs for Model-Based Systems Engineering

YouTube video by JuliaHub

youtube.com

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

SciML Developer Chat Episode 1: Trimming Support and Symbolics Precompilation

YouTube video by The Julia Programming Language

youtu.be

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

Claude Code in Scientific Computing: Experiences Maintaining Julia's SciML Infrastructure - Stochastic Lifestyle

Claude Code in Scientific Computing: Experiences Maintaining Julia’s SciML Infrastructure So it’s pretty public that for about a month now I’ve had 32 processes setup on one of the 64 core 128gb RAM s...

stochasticlifestyle.com

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?...

Demonstration of AI-Assisted Modeling in Dyad with Cursor AI

YouTube video by JuliaHub

youtu.be

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_...

GitHub - SciML/Julia_Modeling_Workshop: High-Performance Scientific Modeling with Julia and SciML

High-Performance Scientific Modeling with Julia and SciML - SciML/Julia_Modeling_Workshop

github.com

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...

A Deep Dive Into DifferentialEquations.jl | JuliaCon Global 2025 | Rackauckas, Smith

YouTube video by The Julia Programming Language

youtube.com