Uploaded March 2026 | Updated September 2026, 2 weeks ago
Fabian Alefeld hosts Duann Scott on the Editor Snack podcast to discuss how AI is evolving in additive manufacturing, moving from “AI-washing” and impractical text-to-mesh hype toward more capable tools using language models, visual language models, surrogate models, and emerging foundational models. Scott describes testing tools by trying to make them fail and highlights a recent success with the Raven plugin for Rhino/Grasshopper, which generated a parametric VESA mount and tripod adapter from minimal prompts, then iteratively added fillets and an isogrid structure and produced a printable part within hours. They discuss constraints like missing engineering training data and design intent, the promise of AI for toolpath and process optimization (including transfer of parameter knowledge across materials), and the role of the 3MF format in capturing toolpath and metadata to enable richer, searchable datasets. Scott previews CDFAM events in Barcelona, DC, and Tokyo and emphasizes that progress requires significant data work and investment.
00:00 Welcome and Guest Intro
02:18 AI Hype to Real Progress
04:13 Testing AI Design Tools
04:46 Data Gaps and Design Intent
07:15 Two Paths for AI Design
10:15 Raven Grasshopper Breakthrough
13:17 Pushing Parametric Complexity
20:28 Limits of Black Box Optimization
22:40 Toolpath and Material Transfer
26:18 Alloy Discovery and Qualification
28:05 3MF Role Teaser
28:18 3MF Format Overview
29:17 Smarter Toolpath Extensions
32:31 Metadata for AI Training
35:43 Data Ownership and Synthetic Data
39:59 AI Impact on Additive
44:10 Workforce and Reshoring
47:22 What Is CDFAM
49:49 CDFAM Audience and Format
51:43 DC Event and Government
54:05 Wrap Up and Thanks
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Fabian Alefeld hosts Duann Scott on the Editor Snack podcast to discuss how AI is evolving in additive manufacturing, moving from “AI-washing” and impractical text-to-mesh hype toward more capable tools using language models, visual language models, surrogate models, and emerging foundational models. Scott describes testing tools by trying to make them fail and highlights a recent success with the Raven plugin for Rhino/Grasshopper, which generated a parametric VESA mount and tripod adapter from minimal prompts, then iteratively added fillets and an isogrid structure and produced a printable part within hours. They discuss constraints like missing engineering training data and design intent, the promise of AI for toolpath and process optimization (including transfer of parameter knowledge across materials), and the role of the 3MF format in capturing toolpath and metadata to enable richer, searchable datasets. Scott previews CDFAM events in Barcelona, DC, and Tokyo and emphasizes that progress requires significant data work and investment.
00:00 Welcome and Guest Intro
02:18 AI Hype to Real Progress
04:13 Testing AI Design Tools
04:46 Data Gaps and Design Intent
07:15 Two Paths for AI Design
10:15 Raven Grasshopper Breakthrough
13:17 Pushing Parametric Complexity
20:28 Limits of Black Box Optimization
22:40 Toolpath and Material Transfer
26:18 Alloy Discovery and Qualification
28:05 3MF Role Teaser
28:18 3MF Format Overview
29:17 Smarter Toolpath Extensions
32:31 Metadata for AI Training
35:43 Data Ownership and Synthetic Data
39:59 AI Impact on Additive
44:10 Workforce and Reshoring
47:22 What Is CDFAM
49:49 CDFAM Audience and Format
51:43 DC Event and Government
54:05 Wrap Up and Thanks
____________________
Subscribe to our YouTube channel:
YouTube: https://www.youtube.com/eosgmbh?sub_c...
Follow us:
LinkedIn: linkedin.com/company/eos
Twitter: twitter.com/eos3dprinting
Instagram: instagram.com/eos3dprinting
____________________
Imprint: eos.info/en/footer/imprint
Privacy Policy: https://www.eos.info/en/footer/privac...
____________________
