Visions: A Machine Vision and Automation Solutions Podcast

Inside Bitsensing's Real-World Deployment of Commercial Vehicle ADAS System

This episode examines Bitsensing's retrofit ADAS kit deployed on passenger buses in South Korea, combining radar, cameras, and AI to increase driver awareness in dense urban traffic. Initial deployment reported results of more than 50% improvement in driver safety scores and a 24% drop in pedestrian collision warnings.
 

Ultra-Long-Range 4D LiDAR for Next-Gen Security

This episode explores SiLC Technologies' Ionic Vista, an ultra-long-range 4D LiDAR vision system built on silicon photonics that provides wide-area coverage beyond a kilometer with per-pixel distance, velocity, and polarization measurements.
Host Jim Tatum speaks with Arlon Martin about the system's features, including dynamic region-of-interest scaling, object detection and identification capabilities, integration with radar and cameras, performance in fog and dust, and how the system supports high-end security and layered sensing solutions.

Embedded AI & Smart Cameras: The Next Decade of Machine Vision

Sharon Spielman interviews Johannes Zurin of Allied Vision about the future of machine vision, covering the rise of embedded AI and smart cameras, new sensor technologies like SWIR, and growth areas such as semiconductors and defense.
The episode also discusses shifting supply chains, pricing pressure, faster development cycles, changing B2B buying behaviors, and the importance of partnerships and industry standards in accelerating adoption.

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.

Cognex Talks AI on the Factory Floor: Part 2

In this episode, the second and final of a two-part podcast, Sharon Spielman interviews Cognex CEO Matt Moschner about a new survey and the real-world impact of AI-driven machine vision. They discuss transparency and auditability for regulated industries, lowering the barrier to adoption through easier-to-deploy AI tools, and advances in embedded hardware that enable higher throughput and better defect detection.
 

Cognex talks AI Vision on the Factory Floor: Part 1

This episode explores Cognex's recent survey on AI-driven machine vision, featuring an interview of Cognex CEO Matt Moschner by Sharon Spielman, VSD's head of content. The discussion covers years of AI tool development, common adoption hurdles, usability and scalability improvements, and industry-specific adoption trends in automotive, electronics, logistics, FMCG, and semiconductors.
Listeners will learn how modern AI vision advances are reducing deployment time, enabling lift-and-shift across global sites, and where adoption is progressing fastest.