Blog posts tagged parquet

Shared vector embeddings updates

There is a lot of ground to cover in this blog post: The Met publishing their own vector embeddings, SFO Museum publishing 1152-dimension vector embeddings for its images, SFO Museum producing 1152-dimension vector embeddings for NGA and MoMA, and a whole bunch of updates to the tooling used to generate and query vector embeddings targeting local-first and consumer-grade hardware.

This is a blog post by aaron cope. It was published on May 27, 2026 and tagged roboteyes, machine-learning, collection, duckdb, golang, parquet, bleve, embeddings, aws, s3 and s3vectors.

OEmbeddings - What is the least amount of metadata necessary for shared vector embeddings?

This is a blog post describing a proposal for a set of common attributes to include with shared vector embeddings. These common attributes are meant to be the least amount of metadata necessary to provide a simple preview and suitable attribution for the item (an image or text) for which vector embeddings have been produced.

This is a blog post by aaron cope. It was published on April 15, 2026 and tagged roboteyes, machine-learning, collection, oembeddings, embeddings, golang and parquet.

Shared cross-institutional vector embeddings – how we might get there

We are proposing a simple‑is‑best approach to sharing vector embeddings of our collections, a step that moves us closer to realizing the long‑standing ‘holy grail’ of cross‑institutional collections search through vector‑based image similarity.”

This is a blog post by aaron cope. It was published on April 06, 2026 and tagged roboteyes, machine-learning, collection, duckdb, golang, parquet and embeddings.