Using computer vision and deep neural networks, the last few years have seen a remarkable growth in the use of AI for mission-critical production solving real-world problems for organizations. These include real-world applications like ,defense, medicine, and transportation.

Many of these applications run on NVIDIA GPUs, which handle multiple tasks such as segmentation, classification, and detection using images and videos for data. However, the most painful and time-consuming part of deploying these deep learning models remains data labeling and data management for training data.

Attendees joined Labelbox and NVIDIA for a training to see how your agency can enable improved accuracy for end models trained on NVIDIA GPUs with Labelbox.

Attendees discover how this solution can:

• Lower the costs of data labeling with a training data platform
• Scale your machine learning workflows in a repeatable manner
• Speed-up your AI and Machine Learning programs to production
• Help you optimize data labeling cost while helping protect and advance the IP or data of your agency while making it ready for AI