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An abstract digital visualization displaying data flow and network connectivity. Glowing lines in blue, red, orange, and yellow stream across a dark blue background filled with binary code, circuit patterns, and data analytics charts. Illuminated dots and nodes cluster on the right side, representing data points or network nodes. The left side shows various digital interface elements including graphs, percentages, and monitoring icons, creating a representation of big data processing, artificial intelligence, or network analysis.

Leveraging know-how with AI into efficient product design

Is your engineering data a hidden goldmine? Overcome the ‘cold start’ problem in AI by using geometric similarity and transfer learning to transform existing models and simulations into powerful assets, speeding up product design and innovation

Your next colleague is an agent: The dawn of agentic AI-aided engineering

What if every engineer had instant access to simulation expertise? Agentic AI-Aided Engineering could transform engineering by putting intelligent AI agents alongside designers, automating complex CAE workflows, and breaking long-standing expertise bottlenecks. Discover how this emerging approach could democratize simulation and accelerate innovation across the engineering lifecycle

Fine-Tuning VLM

When off-the-shelf is not enough: fine-tuning for industrial part classification

Part identification in complex CAD assemblies is a bottleneck in simulation workflows, which can cost engineering teams days before the real work even begins. In this post, we explore how fine-tuning a Vision-Language Model on industrial components can improve the pre-processing phase.

Transfer Learning accelerating the shift to new battery materials and chemistries

Unlock faster battery innovation with transfer learning! This blog reveals how AI accelerates the discovery and optimization of new battery materials, rapidly advancing sustainable energy solutions for a brighter future

Autonomous simulation: From design intent to validated results in less than 60 seconds

What if finishing a design meant receiving a validated simulation report moments later – no mesh generation, no boundary condition setup, no solver configuration required? This is exactly what Siemens’ latest prototype delivers: a simulation co-pilot embedded directly into the Designcenter environment that reasons about geometry, autonomously configures finite element analyses, and produces validated results in under 60 seconds.

Agentic AI for simulation post-processing

Ask, don’t click: Agentic AI takes the pain out of simulation post-processing

Picture this. You have just finished a hydraulic drive-cycle simulation in Simcenter Amesim. The solver finished in four minutes. Excellent….

Optimization workflow for hybrid-electric aircraft using multi-physics simulation, co-simulation, and safety analysis for efficient, resilient design.

From menu to meal: Cooking up a safer hybrid-electric aircraft faster

The skies are changing for the better! Hybrid electric aircraft are revolutionizing air travel, blending electric efficiency with traditional power for a sustainable future. Expect quieter flights, fewer emissions and a giant leap towards eco-friendly aviation. This isn’t just innovation; it’s the dawn of a cleaner, brighter era for how we fly!

ML for Industrial CAE – “Just scale it”

By scaling up ML, engineers can more quickly iterate and optimize their product design, thanks to faster simulations. ML can speed up traditional methods, which makes it easier to integrate their capabilities within established company software and processes. Read about our ML engineering innovation journey in the frame of the research project ML4SIM!

Realizing reliable microelectronic systems

1. Challenge: Microelectronic systems need to be reliable The sustainability of the market for Electronic Components and Systems (ECS) depends…