Siemens Digital Industries Software Blogs

Today's semiconductor market demands ever greater computing power in smaller node sizes, outpacing the growth rate of Moore's Law.

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!

Hannover Messe 2026 is only days away and Siemens will be anchoring Hall 27 with demonstrations of the forefront of AI-assisted manufacturing.

Automotive product development is becoming increasingly complex. Learn how cross-domain design collaboration helps you easily find, share and re-use data.

Hannover Messe is always one of the most exciting moments of the year for the manufacturing community. It brings together...

Artificial intelligence is increasingly moving out of centralized data centers and into the physical systems that generate data. In 2026,...

Humanoid robots are emerging now because technology maturity, workforce needs and economics have all aligned. Combined with labor shortages, and lowering costs of materials, advancements in AI, compute, batteries, sensing and digital engineering are pushing these robots into real production environments.

In the future, robots will be doing everything for us, right? Well, maybe not quite everything. But they’ll most likely...

Make "data the new oil" can be a dangerous analogy for CEOs championing AI efforts. But one important step turns this hallucination into reality.