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Modernizing MLOps at understand.ai with ClearML

Modernizing MLOps at understand.ai with ClearML

At understand.ai, we develop ML-based software to automate data labeling. Our work involves building and maintaining numerous models, which require regular updates and fine-tuning to meet our customers' specific needs. Optimizing our ML operations directly enhances the …

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How to Elevate Autonomous Systems for Industrial Sites: Embotech Case Study

How to Elevate Autonomous Systems for Industrial Sites: Embotech Case Study

In today's evolving industrial landscape, Embotech is a leading provider of AI software for autonomous systems. Headquartered in Zurich, Switzerland, Embotech's solutions enhance safety, productivity, and energy efficiency in logistics yards, ports, and smart factories …

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New tooling for multi-sensor labeling

New tooling for multi-sensor labeling

What Prompted the Need for Updated Labeling Tooling? Modern vehicles can be equipped with a variety of different sensors for assistance systems or autonomous driving. Common examples are cameras, RADAR and LIDAR sensors and many more. While some assistance functions such as an …

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Autonomous Driving: Synthetic Data versus Real Data

Autonomous Driving: Synthetic Data versus Real Data

By · 6 minutes read

Significance of Ground Truth Labels in Machine Learning

Significance of Ground Truth Labels in Machine Learning

· 3 minutes read

Participants of the AVEAS Project workshop discussing the latest developments and key results in autonomous driving technologies.

Workshop for the AVEAS Project. Latest developments and key results

By · 3 minutes read

Graphical representation of the automated annotation system used for scaling ADAS validation, as featured in understand.ai's case study.

Enabling ADAS Validation Scale with Automated Annotation. A case study

By · 5 minutes read