Embedding Dimensions and Synthetic Data
Alex and Bo discuss the implications of high embedding dimensions and the potential cost associated with using them. They also explore the use of synthetic data sets for fine-tuning embedding models, highlighting the surprising success achieved with minimal training steps.In this clip
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Related Questions
What do you know about embedding in vector databases in the context of the episode #60 Geometric Deep Learning Blueprint (Special Edition) and the clip Vector Spaces in Representation Learning?
What do you know about embedding in vector databases in the context of the episode #60 Geometric Deep Learning Blueprint (Special Edition) and the clip Vector Spaces in Representation Learning?