Watch how Dyad's AI agent builds a complete thermal model from just an image! This video demonstrates Dyad's agentic workflow by recreating a coffee cup cooling model
JuliaHub tested the latest frontier models gpt-5.6-sol in its agent, on five modeling and simulation problems of varying difficulty. See the results here.
This video covers various structural simplification algorithms used in ModelingToolkit.jl and the future development goals of ModelingToolkit.
JuliaHub is the enterprise platform behind the Julia language ecosystem, trusted by engineers and scientists building high-performance, production-grade models across aerospace, automotive, energy, manufacturing, and semiconductors.
Watch how AI-powered agentic workflows in Dyad revolutionize model-based systems engineering. In this demonstration, we build a complete friction brake system model—including mechanical dynamics, thermal analysis, and vehicle integration—in just minutes instead of days.
Dyad 3.0 made the agent capable. Dyad 3.1 makes it sharp.
Join the official launch of Dyad 3.0, the next evolution in model-based engineering powered by Scientific AI.
Dyad, the world’s first-to-market agentic AI platform for hardware engineering, brings physical AI to complex systems design and testing, compressing R&D time from months to mere days.
This post demonstrates a single acausal thermal model of a three-zone commercial office building in Dyad, which is run in steady state as well as transient modes.
JuliaHub is the enterprise platform behind the Julia language ecosystem, trusted by engineers and scientists building high-performance, production-grade models across aerospace, automotive, energy, manufacturing, and semiconductors.
This video introduces the Dyad Agent: what it is, how it works, and where it fits into modern model-based engineering workflows.
AI agents can handle physics-based modeling complexity while engineers focus on design judgment and tradeoffs.
Dyad AI enables users to model, simulate, and validate designs using physics-grounded reasoning loops.
Check out these upcoming webinars and workshops from JuliaHub.
In this recorded live session, we explore how to use Dyad’s agentic AI to build and simulate a quadcopter model with real-time interaction using Makie.jl.
The AI for Science environment that integrates coding, simulation, and scientific reasoning into a single engineering workflow.
Physics-informed virtual sensors are shifting condition monitoring from isolated pilots to scalable, physics-based intelligence across assets. Here’s how SciML can help engineers get there.
Learn how Mitsubishi Electric used Dyad workflows with ML to develop a non-invasive state estimation approach. Leveraging pressure and temperature data can predict hard-to-measure system variables with high accuracy, achieving errors of less than 2%.
This video tutorial demonstrates how AI-assisted development can accelerate your Dyad modeling workflow in Julia.
Discover the key differences between causal and acausal modeling approaches and learn why acausal modeling unlocks superior reusability and flexibility in system design.
Learn how to leverage Dyad's model discovery capabilities to automatically identify and complete missing physics in your engineering models using Scientific Machine Learning (SciML) and Universal Differential Equations (UDEs).
At JuliaCon 2025, Aayush Sabharwal presented a talk about the growth of ModelingToolkit over the past couple of years, highlighting new features, improved workflows and documentation and plans for the future.
In this video, you will learn the basics of Dyad and set up your first project. This tutorial takes you through creating a component library, running simulations, and analyzing results.
Discover how Software-Defined Machines are revolutionizing hardware development to match the speed and agility of software engineering.
By combining AI agents with a constrained, unit-tested modeling language, Dyad creates a workflow that doesn't just generate code faster, it generates correct code that's ready for real-world deployment.
By combining SciML, cloud-native workflows, and integrated modeling, tools like Dyad break the barriers between engineers and developers, between fast system models and detailed physics, and between static digital models and evolving digital twins.
At JuliaCon 2025 engineers, researchers, and innovators gathered to explore how Julia is reshaping the future of technical computing.
In a recent webinar, participants walked through the complete journey of building and deploying an active suspension control system. Here's what they learned...
The future will be different, but the engineer will still be in control. And Dyad will be their tool.
The Dyad language is heavily inspired by the Modelica language and the Julia language. So... why not use Modelica or Julia (or Python or MATLAB). This blog explains why we chose to go this route and why we think it is so exciting.
Modern simulation software drives Ai and digital twins for rapid iteration in industrial engineering
Access a growing library of premium Julia resources for free
Physical systems like cars, turbines, robots, or satellites are increasingly being built around digital twins.
This webinar explores how to model, simulate, and analyze both steady-state and dynamic systems using Julia and ModelingToolkit.jl (MTK).
This webinar introduces a smarter approach to system modeling using Dyad, a modern, flexible modeling language built on Julia. Learn how you can design scalable models, starting with a simple RLC circuit, and simulate them in one integrated environment.
There exist several parallel programming paradigms that unlock the potential of modern computing and the Julia Programming language provides built-in support for these paradigms.
This webinar recording introduces Dyad Studio, the newly unveiled (and renamed) VS Code extension from JuliaHub.
Industry luminary Michael Tiller provides a roadmap to navigating the challenges and embracing the opportunities that lie ahead.
Dyad, the world’s first-to-market agentic AI platform for hardware engineering, brings physical AI to complex systems design and testing, compressing … Continue reading JuliaHub raises $65M Series B and launches Dyad 3.0, bringing Agentic AI to Industrial Digital Twins
The AI for Science environment that integrates coding, simulation, and scientific reasoning into a single engineering workflow. CAMBRIDGE, MA; FEBRUARY … Continue reading JuliaHub Launches Dyad AI: The First Agentic Engineering Platform Built for Real-World Physics
Integration of Dyad enables physics-informed AI for simulation-driven innovation Cambridge, MA: JuliaHub, a leader in AI-native simulation and modeling, today … Continue reading JuliaHub Partners with Synopsys to Power SciML-Based Digital Twins
A unified modeling environment that couples orbital analysis with solar panel and power electronics simulation offers a faster, high-fidelity, and mission-relevant way to design and validate spacecraft power systems.
Williams Racing boosts performance with JuliaHub simulations, enhancing strategic race decisions.
Instron Uses Dyad for 500x Faster Design Time, Leading to Faster New Product Design
Zipline uses Julia for aircraft simulation to deliver life-saving emergency medical supplies via drone in Africa and worldwide.
Welcome to Revolution in Simulation, an online community. A one-time registration is needed to provide you with free unrestricted access to all Rev-Sim content and to the quarterly newsletter featuring the latest updates, news, events and more.
Not a Registered Member yet? Register once for a RevSim membership
