Hundreds of petabytes of data are being created by automaker vehicle test fleets during ADAS feature and autonomous vehicle software development, all of which must be tagged, labeled, classified, and validated for accuracy in a cost-efficient and scalable manner to create high-quality training datasets to be used during model and algorithm development stages. Additionally, personally identifiable information (PII) must be anonymized to satisfy compliance requirements defined by European Union’s General Data Protection Regulation (GDPR) or California Consumer Privacy Act (CCPA). These solutions help automakers cost-effectively manage data labeling and anonymization in the AWS cloud through improved automation, tools, and workflows.

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  • Appen Data Annotation Platform

    SaaS product for Data Labeling that delivers controlled, consistent, high-quality annotated data with speed and at scale.
  • Simcenter Autonomy Data Analysis

    Autonomy is a clear direction for our transportation systems, be it mass or personal transit. Physically and virtually evaluating these new vehicles in a live environment ensures rigorous and detailed feedback, giving engineers greater confidence in their design decisions.
  • Sama Pro

    Sama’s integrated ML-powered platform with human-in-the-loop validation streamlines AI development for quicker time to accuracy – and to market.
  • VisionAI Platform

    Empower End-To-End Vision-Focused AI with Data-Centric Insights, Accelerated Model Development and Seamless Edge Integration.
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