Vision-Language Models in Manufacturing

Vision Language Models in Manufacturing: Part 2

Here is the second installment of a two-part podcast on Vision Language Models. In this episode, host Jim Tatum speaks with Dijam Panigrahi, co-founder and COO of GridRaster, about VLMs and their expanding role in machine vision and robotics. The conversation covers real-world deployments in manufacturing and depot environments, how VLMs integrate with quality standards and digital twins to create living systems with traceability and audit logs, and offers practical guidance for plant managers on selecting use cases and measuring ROI. The episode also addresses misconceptions about job loss, emphasizes the human-in-the-loop approach, and highlights how VLMs can improve inspection safety, consistency, and worker productivity.

Vision-Language Models in Manufacturing

In this episode Jim Tatum interviews Dijam Panigrahi of GridRaster about Vision-Language Models (VLMs), a next-generation AI that blends visual data and natural language to enable reasoning, interpretation, and real-time decision-making in industrial settings. VLMs are shown to improve robotics and inspection by giving machines context-aware vision, active task guidance, and expert knowledge to augment human workers and automate complex tasks. The discussion also covers practical challenges, including domain-specific training, compute requirements, edge deployment, and the use of synthetic data to scale VLMs for real-world factory floors.

Visions Podcast: Inside Automate 2026 with Alex Shikany

In this episode, A3 Executive VP Alex Shikany joins Vision Systems Design's head of content Sharon Spielman to preview Automate 2026 in Chicago (June 22–25). They discuss the new Humanoid Robot Forum, the convergence of vision, AI, and robotics, and how standards, interoperability, and practical demos will shape real-world deployments. The conversation highlights key sessions and free expo events—certified vision tracks, innovation stages, demos in the NVIDIA-sponsored pavilion, daily keynotes, and networking opportunities—offering engineers and managers a one-stop view of the latest machine vision and automation trends.

Building Cyber‑Resilient Machine Vision: From Defense to Recovery, Part 2

In this episode of Visions, Sharon Spielman interviews Thomas Hopner of MVTEC about cyber resilience for machine vision systems, covering secure communication and firmware, manual patching constraints due to certifications, and the impact of the EU Cyber Resilience Act. They discuss practical steps—risk assessments, managing open-source dependencies, developer education, containerized CI/CD pipelines, and the challenges of long-term support and balancing compliance with innovation. Part 2 of two installments.

Building Cyber‑Resilient Machine Vision: From Defense to Recovery, Part 1

In this episode of Visions, Sharon Spielman, VSD's head of content, interviews Thomas Hopfner of MVTec, who discusses cyber resilience for machine vision systems, explaining how resilience differs from traditional cybersecurity and why recovery and ongoing patching matter. Hopfner covers practical guidance on secure communication, firmware integrity, software bills of materials (S‑BOMs), and compliance with the EU Cyber Resilience Act, plus MVTec’s approach to patches, support, and customer collaboration. This is Part 1 of a two-part installment.