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Meta-learning with Meteor
In this episode, I caught up with Marc Rußwurm to learn about Meta-learning with Meteor. Our conversation starts with a discussion about meta-learning and the training of Meteor, and how this approach differs from the typical approaches taken to train foundational models. We cover the advantages and challenges of this technique, and discuss the fine-tuning of Meteor with minimal examples—as few as five—for tasks like deforestation monitoring and change detection, and consider what the future could hold for this approach. Meteor showcases the significant potential of few-shot learning for…
The skinny
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