Our October 2025 #newsletter is out! Highlights include: The release of Julia 1.12, featuring --trim for dramatically smaller binaries (down to ∼1MB) and new Pkg features like Workspaces. Dyad's new #Agentic #AI system that ensures physical correctness in complex model-based

The key to overcoming costly, unpredictable system failure isn't just better hardware—it's advanced computational models. Join our upcoming technical #webinar to see a deep-dive demonstration on designing and deploying a robust Predictive Maintenance Solution using #Dyad and

Stop building complex engineering models over days. Start building them in minutes. Our latest demo showcases how Dyad’s AI-powered agentic workflows are fundamentally changing Model-Based Systems Engineering. Watch as we construct a complete friction brake system

The clock is ticking! Are you still letting unpredictable equipment failure dictate your maintenance budget? Every minute of unplanned downtime costs you. This isn't a theory session. Join Dr. Ranjan Anantharaman in this technical deep dive to see exactly how you can implement a

High-Performance Scientific #Modeling with Julia and SciML: This workshop offers in-depth training on advanced scientific computing techniques using the Julia programming language and the SciML (Scientific Machine Learning) ecosystem. https://t.co/yKVIBeoZj7 #JuliaLang #SciML

Stop reacting to system failures and start predicting them. Join Dr. Ranjan Anantharaman for an exclusive technical #webinar on Fault Detection using State Estimators and Digital Twins with #Dyad. We’ll show you how to leverage mathematical state estimation methods to detect

The biggest blocker for AI in Model-Based Engineering isn't speed—it's correctness. Generic AI code can run fast, but does it meet fundamental physical constraints? Dyad flips the script. We embed AI agents within a constrained, unit-tested framework. The AI collaboratively

Happening Now: Open Source Friday is live! If you're involved in high-performance computing, data science, or scientific machine learning, you don't want to miss this deep dive into the Julia Programming Language. Join this talk with Julia's co-creator and JuliaHub CEO, Viral B.

Standard libraries are great, but custom physics is inevitable. Dyad solves the engineer's dilemma by turning domain knowledge into reusable, acausal components. It allows teams to move beyond rigid, proprietary blocks, demonstrating how to assemble a full RLC circuit from

AI-Assisted Modeling in Dyad with Cursor AI We’ve just released a new demo showing how large language models can transform system modeling in Dyad. Highlights include: - AI-guided model exploration and analysis - Intelligent plotting and visualization - Automatic RLC circuit

Stop reinventing the wheel. If you build system models, you know the pain of rewriting the same fundamental equations repeatedly. This post shows how Dyad’s acausal standard libraries accelerate your workflow with ready-to-use components across electrical, mechanical, thermal,

We are thrilled to announce a host of new features making scientific computing on JuliaHub more powerful and seamless. This update focuses on reproducibility, flexibility, and control. We are introducing Time Capsule for immutable job reproduction (key for compliance), built-in

The pressure to optimize IT budgets is real. Many organizations are migrating from licensed compute to flexible, hybrid models. But how do you maintain #performance while controlling cloud costs? Join us for this #webinar as we walk through a migration that achieves both goals.

Building high-fidelity models shouldn't mean reinventing the wheel. This video explores how #Dyad's standard libraries accelerate your workflow with ready-to-use components across electrical, mechanical, and fluid domains. Using a DC Motor model, you'll see how to select

We are proud to announce the first stable release of Dyad Studio, version 1.0.0! This major milestone brings a host of new features that enhance productivity and streamline #modeling workflows. Highlights include a native Model Context Protocol server for AI integration, support

Julia and ModelingToolkit.jl are a powerful combination for engineers. This video explores how to model and analyze both steady-state and dynamic systems. You'll see how to efficiently set up, solve, and interpret system responses, using a hydraulic actuator model as a

Major news for engineers and researchers! A recent talk on ModelingToolkit.jl highlighted new features that simplify workflows and boost performance. MTKParameters enables parameter #optimization, while improved initialization allows for a wider range of initial conditions. The

Modeling complex systems can be challenging, but we can help. Get a free modeling problem review with one of our experts to get hands-on guidance tailored to your work. Whether you're building physical models or digital twins, our experts can suggest workflows and highlight

Are you frustrated with large, slow model exports? A major improvement to the way Functional Mockup Units (FMUs) are generated has arrived. A new workflow, leveraging Julia 1.12, generates much smaller FMUs (~55 MB) and is significantly faster (~2 min compilation time). This is a