Overview of maximizing the potential of the FiftyOne open-source SDK and App to efficiently store and annotate training data for Generative AI workflows, including cloud-based storage/hosting architecture, training/apply models for semi-automatic data annotation, and CVAT integration for pixel-perfect side-by-side evaluation.
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Speaker
Maxime Brénon
3
talks
machine learning and data engineer
Maxime Brénon is a machine learning and data engineer. An Xoogler he started his machine learning journey at Moodstocks when AlexNet was all the rage.
Bio from: Feb 20 - Virtual AI, ML and Computer Vision Meetup
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In this talk we’ll explore how we maximize the potential of the FiftyOne open source SDK and App to efficiently store and annotate training data critical to Finegrain’s Generative AI workflows. We will provide an overview of our cloud-based storage and hosting architecture, showcase how we leverage FiftyOne for training and applying models for semi-automatic data annotation, and demonstrate how we extend the CVAT integration to enable pixel-perfect side-by-side evaluation of our Generative AI models.
In this talk we’ll explore how we maximize the potential of the FiftyOne open source SDK and App to efficiently store and annotate training data critical to Finegrain’s Generative AI workflows. We will provide an overview of our cloud-based storage and hosting architecture, showcase how we leverage FiftyOne for training and applying models for semi-automatic data annotation, and demonstrate how we extend the CVAT integration to enable pixel-perfect side-by-side evaluation of our Generative AI models.