aiData introduces a fully automated data pipeline designed to streamline the workflow of automotive Machine Learning Operations (MLOps) for ADAS and autonomous driving development. Recognizing the enormous task of processing millions of kilometers of driving data, aiData employs automation from data collection to curation, annotation, and validation, enhancing the efficiency of data scientists and engineers. This crafted pipeline not only facilitates faster prototyping but also ensures higher quality in deploying machine learning models for autonomous applications.
Key components of aiData include the aiData Versioning System, which provides comprehensive transparency and traceability over the data handling process, from recording to training dataset creation. This system efficiently manages metadata, which is integral for diverse use-cases, through advanced scene and context-based querying. In conjunction with the aiData Recorder, aiData automates data collection with precise sensor calibration and synchronization, significantly improving the quality of data for testing and validation.
The aiData Auto Annotator further enhances operational efficiency by handling the traditionally labor-intensive process of data annotation using sophisticated AI algorithms. This process extends to multi-sensor data, offering high precision in dynamic and static object detection. Moreover, aiData Metrics tool evaluates neural network performance against baseline requirements, instantly detecting data gaps to optimize future data collection strategies. This makes aiData an essential tool for companies looking to enhance AI-driven driving solutions with robust, real-world data.
