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Tengyu Ma on Voyage AI - Weaviate Podcast #91!

Weaviate Podcast

CHAPTER

Fine-Tuning and Scaling Laws in AI Embedding Models

The chapter explores the importance of predictability and efficiency in large AI embedding models, emphasizing the challenges of balancing model size for faster processing without compromising accuracy. It discusses the process of fine-tuning embedding models on Langchain documentation for improved retrieval quality and highlights the implications of overfitting, zero shot learning, and continual fine-tuning in adapting models to evolving data sets.

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