# Embeddings

- Page: https://shared.btbytes.com/p/embeddings
- Date: 2025-06-25

- [Word Embedding Analysis](http://wordvec.colorado.edu/index.html) --  provides semantic analysis tools based on high-dimensional vector space word embeddings, combining updated features. You can play around the online tools to see how the different techniques work.
- [What are embeddings?](https://vickiboykis.com/what_are_embeddings/) book/paper by Vicki Boykis; May 2023. 
- [What are embeddings in machine learning? | Cloudflare](https://www.cloudflare.com/learning/ai/what-are-embeddings/)
- [Embeddings  |  Machine Learning  |  Google for Developers](https://developers.google.com/machine-learning/crash-course/embeddings)
- [Vector embeddings - OpenAI API](https://platform.openai.com/docs/guides/embeddings)
- [How big are our embeddings now and why?](https://vickiboykis.com/2025/09/01/how-big-are-our-embeddings-now-and-why/) by Vicki Boykis; Sep 2025.

## Tools

[Embedding Atlas](https://apple.github.io/embedding-atlas/overview.html)  is a tool from Apple that provides interactive visualizations for large embeddings. It allows you to visualize, cross-filter, and search embeddings and metadata.

>  Nice exploration UX with hover and tool tip for single data points. Shows you nearest neighbors, which is cool. Coloring based on metadata for better insights -- [via](https://x.com/helloiamleonie/status/1954936161085890832)

> [A notebook showing how you can visualize the data stored in Weaviate vector database with Embedding Atlas](https://github.com/weaviate/recipes/blob/main/integrations/operations/apple/embedding_visualization_embedding_atlas.ipynb)

## Papers

([Weller et al. 2025](https://arxiv.org/abs/2508.21038))

![](https://files.btbytes.com/screenshots/2025/embedding-bm25-01.png)


## References

- Weller, Boratko, Naim, Lee (2025). [On the Theoretical Limitations of Embedding-Based Retrieval](https://arxiv.org/abs/2508.21038).