One AI model isn’t enough? Stack a Cascade of brains!

In the non-distant future, we will enter our autonomous car and get to our destination, with driving managed by “AI”. Our self-driving car won’t rely on a single AI model: one model may be capable of identifying road signs, but that alone is not enough. To ensure you get to your destination safely, the car needs to detect other vehicles, pedestrians, and assess in real-time road conditions. Using multiple AI models allows specialization – one model can focus on object detection, while other evaluate road conditions, navigate obstacles, etc. These combined models all contribute to a safer autonomous vehicle experience.

In today’s manufacturing environment, we are still mostly reliant on the “one AI will do it all” framework.  AI-based inspection systems often rely on a single model to handle all aspects of a visual inspection, whether detecting objects, identifying anomalies, or classifying defects. However, this approach can struggle to meet the needs of today’s production lines, especially in industries where products have intricate designs or require different inspection criteria.

Meet Neurala’s Cascade, a new feature part of the VIA suite, designed to leverage the power of multiple AI models stacked within a single workflow, allowing manufacturers to perform complex inspections without sacrificing speed or precision.

Cascade integrates multiple AI models into a stacked workflow, offering a modular solution that allows each model to focus on a specialized task. This approach yields better accuracy and adaptability to real-world scenarios.

How does Cascade work? This is an example

1. Object Detection: the first AI model detects objects of interest within the product.

2. Zoom-In Anomaly Detection: VIA then passes the image data to a second AI model that performs a detailed analysis of these regions to identify even the smallest anomalies or defects, especially in areas prone to imperfections.

3. Custom Workflows: Cascade’s flexibility allows manufacturers to create custom workflows, stacking models in a way that meets their specific inspection needs.

Why is this important to Manufacturers?

Cascade allows for a crucial benefit: increased accuracy. Since each AI model is highly specialized, the combination of several specialized AI model can deliver greater precision in detecting defects than a single one. In addition, Cascade allows reduced training time. Since multiple models can each focus on a smaller aspect of the overall task, this reduces the amount of data and training time required.

Finally, Cascade allows to get more return from your hardware! It optimizes camera utilization, maximizing the use of high-resolution cameras by focusing on key areas for further inspection.

Industries that deal with high-precision manufacturing — such as automotive and pharmaceuticals, — are particularly well-suited to benefit from Cascade’s multi-model workflow. For instance, in drug manufacturing, the first AI model could detect the presence of capsules on a production line, and a second could zoom in to make sure the capsules are sealed correctly or do a final model checks for minute cracks or imperfections in the coating that could affect quality. In automotive, an initial AI model could identify the presence of engine parts, and another could inspect welds on the frame or check for microscopic defects in metal surfaces that could compromise durability.

With Cascade, Neurala’s customers enter the future of AI-powered visual inspection, where multiple AI models work together to tackle complex tasks with ease and precision. By fully utilizing available hardware, Cascade keeps inspection costs low while delivering highly accurate results. This multi-AI approach greatly enhances the efficiency and scalability of inspections, making sure manufacturers stay ahead in today’s highly dynamic production environments.

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For more information, visit Neurala’s website: https://www.businesswire.com/news/home/20241001336553/en/Neurala-to-Launch-Cascade-Feature-at-VISION-Stuttgart.