Dyad 3.2 With More LLMS and Better Visualization: Dyad 3.2 offers a larger choice of models, including OpenAI’s GPT-5 (5.4 and 5.5) alongside Claude. This release also opens the door for other model families in the future. Plus, the graphical editor, analysis points and array connectors are now visualized, making larger models easier to build and read on the canvas. Find out more.
JuliaHub at JuliaCon 2026: Join us at JuliaCon 2026, taking place August 10–15 at Johannes Gutenberg University in Mainz, Germany. This year's conference features a strong lineup of talks from the JuliaHub team, including the annual State of Julia presentation highlighting the latest developments across the Julia ecosystem. Find out more.
Discovering Missing Physics: Why Your CAE Models Fall Short and How the Dyad Agent Fixes This: Traditional Computer Assisted Engineering (CAE) models rely heavily on idealized first-principles physics equations. While they are interpretable, they tend to fall short when dealing with the messy and non-linear realities of the physical world. In this technical brief, we explore how SciML and the Dyad Agent combine the structural certainty of physics with the adaptive power of neural networks to capture "missing physics". Download it here.
AI & Data-Driven Simulation Forum 2026: Join JuliaHub at the AI & Data-Driven Simulation Forum 2026 on 15th July in Neckarsulm, Germany, where industry leaders and engineering experts will explore how AI is transforming modeling and simulation. Discover how agentic AI, digital engineering, and data-driven simulation are accelerating product development, improving engineering workflows, and enabling smarter, faster design decisions. Connect with the JuliaHub team to learn how next-generation AI-powered simulation is shaping the future of engineering.
Revise.jl Upgrades: Smoother Event-Handling & Julia 1.12+ Power: The latest updates to Revise.jl bring massive quality-of-life improvements, focusing heavily on bulletproof event-handling and deeper integration with Julia 1.12+. Development is now significantly smoother thanks to persistent directory monitoring that eliminates dropped filesystem events, a new polling fallback for tracking Windows files under WSL, and a grace period for vanishing/reappearing paths during git checkouts or builds.
Free Online Julia Webinars from JuliaHub: JuliaHub provides free one-hour Webinars led by JuliaHub staff and other experts. Space is limited and registration is required, so please sign up today!
Agentic Simulation of Activated Sludge: Model to Insight with David Dinh and John Batteh, Wednesday July 22, 12 PM (Eastern US)
Autonomous HL‑20 Model Creation: From Specification to Simulation with David Dinh and Rajeev Voleti, Wednesday July 29, 12 PM(Eastern US)
Recent JuliaHub Webinars: JuliaHub provides free one-hour Webinars on topics of interest to Julia users. Nearly 100 past Webinars are available online. Click here to watch.
This Month in Julia World: This Month in Julia World is a newsletter from Stefan Krastanov with up-to-date information about Julia events, new releases and more. Read it here.
Nouvelles Julia - Julia News en Français: Nouvelles Julia is a newsletter in French with the latest Julia news. Read it here.
New Blog Posts from SciML: SciML has published new blog posts. You can read them here.
Julia Dispatch Podcast: Julia Dispatch is a Julia podcast from Dr. Chris Rackauckas (JuliaHub VP of Modeling and Simulation) and Dr. Michael Tiemann. Watch it here.
JuliaHub Digital Twin Solutions and Consulting: We help enterprises build deployable and scalable solutions leveraging SciML to create highly accurate and trustworthy Digital Twins. Applications span asset health monitoring, optimization and predictive maintenance, process optimization, model-based control, design optimization, and internal or external simulation tools. We also offer consulting and technical support. Schedule a consultation with our solutions team to discuss your use case.
Careers at JuliaHub: JuliaHub is a fast-growing tech company with fully remote employees in 20 countries on 6 continents. Click here to learn more about exciting careers and internships with JuliaHub.
Julia Expertise Needed at University of Glasgow: Dr. Eric Silverman, Research Fellow at the University of Glasgow, seeks a Research Associate for a 5-year research project on computational modeling for public health using an agent-based modeling framework developed in Julia. Julia experience and a PhD are required for this position. Click here for more information and to apply.
Julia and JuliaHub in the News
Designing AI‑Ready Public Infrastructure: Global Lessons from India’s Aadhaar Builder
JuliaHub Advances Dyad and SciML Ecosystem Tools to Target High Value Engineering Markets
ORNL debuts JACC for performance-portable Julia for HPC systems
Julia Blog Posts
AMDGPU.jl 2.6 and 2.7: linear algebra, sparse arrays, and RDNA4 matrix cores (Ludovic Räss)
This Month in Julia World (Stefan Krastanov)
Nouvelles Julia (Pierre Navaro)
Metal.jl 1.10: Linear algebra, FFTs, and a faster runtime (Christian Guinard, Tim Besard)
Dyad 3.1: From Smart to Sharper (Mridul Upadhyay)
Rethinking Physical Modeling: Moving Beyond Blocks and Math (Dr. Michael Tiller)
Discovering Missing Physics: Why Your CAE Models Fall Short (and How the Dyad Agent Fixes it) (Dr. Michael Hoffmann)
SciML Small Grants Program: Two Years In, Eight More Projects Funded and Shipped (SciML News)
Solving Complex PDEs in Julia (Sanjana Salkar)
Dyad 3.2: More LLMs, Clearer Diagrams (Mridul Upadhyay)
Neural ODEs, PINNs, and UDEs: A Beginner’s Guide to AI-Augmented Science (Sanjana Salkar)
Julia: Working with vectors and matrices — Part 1 (Ângelo Galvão)
Julia: Working with vectors and matrices — Part 2 (Ângelo Galvão)
Modding My Web Framework With An API Router (Emma Boudreau)
Upcoming Julia and JuliaHub Events
Online: Agentic Simulation of Activated Sludge: Model to Insight with David Dinh and John Batteh, Wednesday July 22, 12 PM (Eastern US)
Online: Autonomous HL‑20 Model Creation: From Specification to Simulation with David Dinh and Rajeev Voleti, Wednesday July 29, 12 PM(Eastern US)
Neckarsulm, Germany: AI & Data-Driven Simulation Forum 2026 with JuliaHub, July 15, 2026
Johannes Gutenberg University Mainz (Germany, near Frankfurt): JuliaCon 2026 with JuliHub, August 10-15
Contact Us: Please contact us if you want to:
Obtain pricing for Dyad and Julia consulting projects for your organization
Schedule Dyad or Julia training
Share information about exciting new Julia case studies or use cases
Partner with JuliaHub to organize a Julia event online or offline
About JuliaHub, Julia and Dyad
Dyad combines physics-based modeling with scientific machine learning(SciML) for mission-critical engineering. Dyad is fully agentic in its design, making it possible for engineers to carry out complex workflows through natural language interaction. Dyad integrates code, diagrams and agentic workflows in a seamless tool driving 10x productivity. Leveraging the Julia and the SciML ecosystem under the hood, Dyad also benefits from significantly higher performance compared to the competition, often being 100x faster at simulating complex physics. Teams leverage Dyad to build smarter, faster, and more reliable systems without compromising the rigor of traditional engineering, supporting use cases from predictive maintenance to real-time performance tuning and over-the-air updates. The Dyad tool powered by Julia and SciML is free to use. Get started here.
JuliaHub is a fast and easy-to-use code-to-cloud platform that accelerates the development and deployment of Julia programs. JuliaHub users include some of the most innovative companies in a range of industries including pharmaceuticals, automotive, energy, manufacturing, and semiconductor design and manufacture.
Julia is a high performance open source programming language that powers computationally demanding applications in modeling and simulation, drug development, design of multi-physical systems, electronic design automation, big data analytics, scientific machine learning and artificial intelligence. Julia solves the two language problem by combining the ease of use of Python and R with the speed of C++. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. Julia has been downloaded by users at more than 10,000 companies and is used at more than 1,500 universities. Julia co-creators are the winners of the prestigious James H. Wilkinson Prize for Numerical Software and the Sidney Fernbach Award.
