AI-powered
podcast player
Listen to all your favourite podcasts with AI-powered features
Weaviate Podcast
Matryoshka Embeddings with Aditya Kusupati, Zach Nussbaum, and Zain Hasan - Weaviate Podcast #89!
Feb 20, 2024
Join the 89th Weaviate Podcast on Matryoshka Embeddings with Aditya Kusupati, Zach Nussbaum, and Zain Hasan. Learn about challenges in training Matryoshka embeddings, experiences building embeddings API, Aditya's research on differentiable ANN indexes, and more!
01:12:14
Episode guests
AI Summary
Highlights
AI Chapters
Episode notes
Podcast summary created with Snipd AI
Quick takeaways
- Efficient training through Matryoshka representations balances dimensionality reduction with performance in embedding models.
- Dynamic weighting of loss functions using adaptive approaches optimizes information encoding across varying embedding dimensions.
Deep dives
Matrioshka Representations in Embedding Models
Training embedding models with matrioshka representations allows for greater efficiency by reducing dimensionality while maintaining performance. By adapting pre-existing models with matrioshka loss, storage and search can become faster and more cost-effective, providing a valuable trade-off between size and quality.
Get the Snipd
podcast app
Unlock the knowledge in podcasts with the podcast player of the future.
AI-powered
Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any
moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
Share
& Export
Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
AI-powered
podcast player
Listen to all your favourite podcasts with AI-powered features
Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode