Intel OpenVINO DevCon Watch Party

WATCH PARTY:

Learn from Ultralytics and Intel® AI experts working side by side in this hands-on session and discover how to build production-ready computer vision pipelines for real-world manufacturing and industrial scenarios. We’ll guide you through a complete, end-to-end object detection workflow—from dataset creation and model training to optimization and edge deployment.

Start by rapidly annotating and iteratively refining image labels with Geti™, enabling efficient dataset bootstrapping even with limited data. Using this dataset, we’ll fine-tune an Ultralytics YOLO26 model for custom object detection—using hazelnuts as a practical example of common manufacturing inspection tasks. The trained model is then converted and optimized with OpenVINO™, leveraging techniques such as hardware acceleration and precision optimization to achieve low-latency inference. Finally, we’ll deploy and benchmark the solution on Intel® Core™ Processors Series 2 and Intel® Core™ Ultra processors, highlighting key considerations for latency, throughput, and resource utilization in edge environments.

Developers will leave with actionable insights to build industrial-grade AI pipelines:

• End-to-End Solution: From image annotation to edge deployment, making vision AI practical for real-world applications.
• Industrial Relevance: Apply object detection to manufacturing and inspection tasks to boost automation and efficiency.
• Rapid Development: Accelerate dataset creation using Geti™, reducing time-to-deployment.
• Optimized Edge AI: Deploy high-performance models with OpenVINO on Intel® hardware for low-latency, efficient inference.

Plus interactive demonstrations of OpenVINO AI models running on Intel AI PC by Adam Milton-Barker.