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This talk explores how we generate high-performance computer vision datasets from CAD—without real-world images or manual labeling. We’ll walk through our synthetic data pipeline, including CPU-optimized defect simulation, material variation, and lighting workflows that scale to thousands of renders per part. While Blender plays a role, our focus is on how industrial data (like STEP files) and procedural generation unlock fast, flexible training sets for manufacturing QA, even on modest hardware. If you're working at the edge of 3D, automation, and vision AI—this is for you!

This talk explores how we generate high-performance computer vision datasets from CAD—without real-world images or manual labeling. We’ll walk through our synthetic data pipeline, including CPU-optimized defect simulation, material variation, and lighting workflows that scale to thousands of renders per part. While Blender plays a role, our focus is on how industrial data (like STEP files) and procedural generation unlock fast, flexible training sets for manufacturing QA, even on modest hardware. If you're working at the edge of 3D, automation, and vision AI—this is for you!

Computer vision is becoming a key enabler of smart manufacturing, from quality inspection to robotic automation. Yet traditional development of AI models often requires large datasets, specialized expertise, and significant time. In this talk, we explore how no-code computer vision platforms are changing this landscape allowing engineers, operators, and domain experts to build, train, and deploy models without deep AI backgrounds. We’ll look at real examples from manufacturing and robotics to show how faster iteration, simpler data workflows, and scalable deployment can move automation projects from concept to production.

Manufacturing and logistics companies face increasingly complex operational challenges that traditional AI and human planning struggle to solve effectively. Collide Technology harnesses Swarm Intelligence algorithms to transform intractable problems—like scheduling hundreds or thousands of maintenance employees while simultaneously optimizing production capacity, inventory levels, and cross-sector resource allocation—into solutions delivered in seconds rather than weeks.

Unlike rigid Operations Research approaches that require specialized expertise and expensive implementations, our platform democratizes industrial optimization by making sophisticated decision-making accessible to any factory or logistics operation. We deliver holistic, data-driven solutions that optimize across multiple business entities and sectors simultaneously, adapting to real-world constraints and evolving operational needs.

This talk explores how we generate high-performance computer vision datasets from CAD—without real-world images or manual labeling. We’ll walk through our synthetic data pipeline, including CPU-optimized defect simulation, material variation, and lighting workflows that scale to thousands of renders per part. While Blender plays a role, our focus is on how industrial data (like STEP files) and procedural generation unlock fast, flexible training sets for manufacturing QA, even on modest hardware. If you're working at the edge of 3D, automation, and vision AI—this is for you!

Anomaly detection is one of computer vision's most exciting and essential challenges today. From spotting subtle defects in manufacturing to identifying edge cases in model behavior, it is one of computer vision's most exciting and crucial challenges. In this session, we’ll do a hands-on walkthrough using the MVTec AD dataset, showcasing real-world workflows for data curation, exploration, and model evaluation. We’ll also explore the power of embedding visualizations and similarity searches to uncover hidden patterns and surface anomalies that often go unnoticed.

This session is packed with actionable strategies to help you make sense of your data and build more robust, reliable models. Join us as we connect the dots between data, models, and real-world deployment—alongside other experts driving innovation in anomaly detection.

Manufacturing and logistics companies face increasingly complex operational challenges that traditional AI and human planning struggle to solve effectively. Collide Technology harnesses Swarm Intelligence algorithms to transform intractable problems—like scheduling hundreds or thousands of maintenance employees while simultaneously optimizing production capacity, inventory levels, and cross-sector resource allocation—into solutions delivered in seconds rather than weeks.

Anomaly detection is one of computer vision's most exciting and essential challenges today. From spotting subtle defects in manufacturing to identifying edge cases in model behavior, it is one of computer vision's most exciting and crucial challenges. In this session, we’ll do a hands-on walkthrough using the MVTec AD dataset, showcasing real-world workflows for data curation, exploration, and model evaluation. We’ll also explore the power of embedding visualizations and similarity searches to uncover hidden patterns and surface anomalies that often go unnoticed.

This talk explores how we generate high-performance computer vision datasets from CAD—without real-world images or manual labeling. We’ll walk through our synthetic data pipeline, including CPU-optimized defect simulation, material variation, and lighting workflows that scale to thousands of renders per part. While Blender plays a role, our focus is on how industrial data (like STEP files) and procedural generation unlock fast, flexible training sets for manufacturing QA, even on modest hardware. If you're working at the edge of 3D, automation, and vision AI—this is for you!

Manufacturing and logistics companies face increasingly complex operational challenges that traditional AI and human planning struggle to solve effectively. Collide Technology harnesses Swarm Intelligence algorithms to transform intractable problems—like scheduling hundreds or thousands of maintenance employees while simultaneously optimizing production capacity, inventory levels, and cross-sector resource allocation—into solutions delivered in seconds rather than weeks.

Unlike rigid Operations Research approaches that require specialized expertise and expensive implementations, our platform democratizes industrial optimization by making sophisticated decision-making accessible to any factory or logistics operation. We deliver holistic, data-driven solutions that optimize across multiple business entities and sectors simultaneously, adapting to real-world constraints and evolving operational needs.

This talk explores how we generate high-performance computer vision datasets from CAD—without real-world images or manual labeling. We’ll walk through our synthetic data pipeline, including CPU-optimized defect simulation, material variation, and lighting workflows that scale to thousands of renders per part. While Blender plays a role, our focus is on how industrial data (like STEP files) and procedural generation unlock fast, flexible training sets for manufacturing QA, even on modest hardware. If you're working at the edge of 3D, automation, and vision AI—this is for you!

Manufacturing and logistics companies face increasingly complex operational challenges that traditional AI and human planning struggle to solve effectively. Collide Technology harnesses Swarm Intelligence algorithms to transform intractable problems—like scheduling hundreds or thousands of maintenance employees while simultaneously optimizing production capacity, inventory levels, and cross-sector resource allocation—into solutions delivered in seconds rather than weeks. Unlike rigid Operations Research approaches that require specialized expertise and expensive implementations, our platform democratizes industrial optimization by making sophisticated decision-making accessible to any factory or logistics operation. We deliver holistic, data-driven solutions that optimize across multiple business entities and sectors simultaneously, adapting to real-world constraints and evolving operational needs.

This talk explores how we generate high-performance computer vision datasets from CAD—without real-world images or manual labeling. We’ll walk through our synthetic data pipeline, including CPU-optimized defect simulation, material variation, and lighting workflows that scale to thousands of renders per part. While Blender plays a role, our focus is on how industrial data (like STEP files) and procedural generation unlock fast, flexible training sets for manufacturing QA, even on modest hardware. If you're working at the edge of 3D, automation, and vision AI—this is for you!

Anomaly detection is one of computer vision's most exciting and essential challenges today. From spotting subtle defects in manufacturing to identifying edge cases in model behavior, it is one of computer vision's most exciting and crucial challenges. In this session, we’ll do a hands-on walkthrough using the MVTec AD dataset, showcasing real-world workflows for data curation, exploration, and model evaluation. We’ll also explore the power of embedding visualizations and similarity searches to uncover hidden patterns and surface anomalies that often go unnoticed. This session is packed with actionable strategies to help you make sense of your data and build more robust, reliable models. Join us as we connect the dots between data, models, and real-world deployment—alongside other experts driving innovation in anomaly detection.

Manufacturing and logistics companies face increasingly complex operational challenges that traditional AI and human planning struggle to solve effectively. Collide Technology harnesses Swarm Intelligence algorithms to transform intractable problems—like scheduling hundreds or thousands of maintenance employees while simultaneously optimizing production capacity, inventory levels, and cross-sector resource allocation—into solutions delivered in seconds rather than weeks. Unlike rigid Operations Research approaches that require specialized expertise and expensive implementations, our platform democratizes industrial optimization by making sophisticated decision-making accessible to any factory or logistics operation. We deliver holistic, data-driven solutions that optimize across multiple business entities and sectors simultaneously, adapting to real-world constraints and evolving operational needs.

Anomaly detection is one of computer vision's most exciting and essential challenges today. From spotting subtle defects in manufacturing to identifying edge cases in model behavior, it is one of computer vision's most exciting and crucial challenges. In this session, we’ll do a hands-on walkthrough using the MVTec AD dataset, showcasing real-world workflows for data curation, exploration, and model evaluation. We’ll also explore the power of embedding visualizations and similarity searches to uncover hidden patterns and surface anomalies that often go unnoticed.

This session is packed with actionable strategies to help you make sense of your data and build more robust, reliable models. Join us as we connect the dots between data, models, and real-world deployment—alongside other experts driving innovation in anomaly detection.