PCB Designers Who Leverage AI May Outperform Others

For years, artificial intelligence (AI) has hovered around the edges of #additivemanufacturing, but the tools that once felt like experiments are now solving real problems. AI could very well be the next big shift in #AM. If you want to see how fast that shift is happening, one of the best places to look is RAPID + TCT 2026 in Boston next month. Vanesa M. Listek reports.

For years, artificial intelligence (AI) has hovered around the edges of #additivemanufacturing, but the tools that once felt like experiments are now solving real problems. AI could very well be the next big shift in #AM. If you want to see how fast that shift is happening, one of the best places to look is RAPID + TCT 2026 in Boston next month. Vanesa M. Listek reports.

For years, artificial intelligence (AI) has hovered around the edges of #additivemanufacturing, but the tools that once felt like experiments are now solving real problems. AI could very well be the next big shift in #AM. If you want to see how fast that shift is happening, one of the best places to look is RAPID + TCT 2026 in Boston next month. Vanesa M. Listek reports.

Everyone is hyping AI and Generative AI like it will replace engineers and start doing CAD design on its own. Let’s be real—it won’t. AI can give you concepts. It can suggest shapes. It can even generate fancy-looking models. But can it: • Decide the right tolerance for assembly? • Understand real-world load conditions and failure modes? • Balance manufacturability, cost, and performance? • Take responsibility when a design fails on the shop floor? No. Because engineering is not just design—it’s accountability. A CAD model that “looks correct” is very different from a design that actually works in production. Generative AI is a tool—not a replacement. It can speed up thinking, but it cannot replace experience, judgment, and practical engineering knowledge. The real risk is not AI replacing engineers. The real risk is engineers blindly trusting AI without understanding fundamentals. Use AI. Leverage it. But don’t depend on it. Because at the end of the day— AI doesn’t sign off designs. Engineers do. #AI #GenerativeAI #MechanicalEngineering #CAD #EngineeringTruth #ProductDesign #Innovation

Dassault Systèmes made a bold case on how AI could reshape packaging machine design at #3DExperienceWorld2026, focusing on capturing existing institutional knowledge, validating designs, and retaining critical engineering insights. Read more ⬇️ #engineering #ai #digitaltransformation #packaging

I asked AI this and the answer is close to how I have been seeing its effective use in my current AI & ART series on IG. Not exactly but very close to what I have been experiencing with my use of AI to help create. Would Leonardo da Vinci have used AI if it existed? Very likely—yes. But not in the way people often imagine. Based on his documented working habits, Leonardo would almost certainly have treated AI as an exploratory instrument, similar to how he used optics, geometry, anatomy studies, and mechanical prototypes. 1. Leonardo aggressively adopted new tools Leonardo constantly incorporated the most advanced technology available in the late 15th century: Advanced optics and perspective systems for painting Anatomical dissection for realism in figures Hydraulic and mechanical engineering for machines and infrastructure Experimental materials in works like The Last Supper His notebooks show a pattern: observe → model → iterate → visualize. AI fits almost perfectly into that workflow. 2. AI would match his “idea amplification” style Leonardo produced thousands of exploratory sketches for concepts like: flying machines armored vehicles anatomical studies city infrastructure Most were conceptual prototypes, not finished works. Modern generative AI is essentially a rapid ideation engine, which aligns with how he worked. He likely would have used AI for: Rapid visual iteration of mechanical ideas Simulating fluid dynamics or flight concepts Exploring variations of compositions before painting Generating anatomical reference hypotheses 3. But he probably wouldn’t rely on it for final work Leonardo valued direct observation above everything. He spent years studying real anatomy, light, and motion. Even if AI suggested ideas, he would almost certainly verify them empirically. Think of AI as something he would treat like: a sketch assistant a mechanical calculator a speculative model generator —not an authority. 4. Historically, he loved “thinking machines” Leonardo designed devices that were essentially analog computation tools: gear-driven calculators programmable mechanical devices early robotic concepts (his famous mechanical knight) If you handed him AI, he’d likely ask: “How does it reason? What mechanism produces the answer?” He would probably try to reverse-engineer it. 5. The paradox: he might also distrust it Leonardo believed knowledge must come from experience (esperienza). If AI produced results without explanation, he might consider it intellectually suspicious until he understood the mechanism. Given AI wrote this answer - I agree with much of it but what is iterated here 5. PARADOX - the mistrust of the tool UNTIL the understanding of HOW IT WORKS. The opportunity to advocate something this new and powerful, comes along once in a lifetime.

Synopsys bets on "agentic engineering" to boost productivity, but AI-driven gains remain uneven, compute-heavy, and not fully proven. #AI #AgenticAI

From parameter calibration to how certain materials behave in certain environments, the expertise that #additivemanufacturing has long relied on is very difficult to document. Le'ora Lichtenstein, CFA, Co-Founder and CEO of Corbel, discusses how this "tribal knowledge" crisis in our industry can't be solved without AI.

From parameter calibration to how certain materials behave in certain environments, the expertise that #additivemanufacturing has long relied on is very difficult to document. Le'ora Lichtenstein, CFA, Co-Founder and CEO of Corbel, discusses how this "tribal knowledge" crisis in our industry can't be solved without AI.

From parameter calibration to how certain materials behave in certain environments, the expertise that #additivemanufacturing has long relied on is very difficult to document. Le'ora Lichtenstein, CFA, Co-Founder and CEO of Corbel, discusses how this "tribal knowledge" crisis in our industry can't be solved without AI.