AI models work best when they are trained on data that is as similar as possible to your real world data in application. The AI hypervisor approach many factors related to your data and its attributes, then selects the optimized model match for your job. This approach allows top tier performance models to always be applied appropriately.
Performance optimization
- Models’ selection is based on point cloud density, sensor type, georegistration and more.
- Combination of machine learning and automatically selected algorithmic techniques that extract maximum value from the data available.
- Ever-expanding number of models and training sets for novel use cases and situations.