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thisisaaronland

@thisisaaronland@orthis.social
mastodon 4.7.3
  • Open on orthis.social

museums and maps / also @orthat@orthis.social

563 Followers
336 Following
11 Posts
Joined November 04, 2022
weblog:
https://www.aaronland.info/weblog
orthis:
https://www.aaronland.info/orthis
whosonfirst:
https://www.whosonfirst.org/
thedayjob:
https://millsfield.sfomuseum.org/blog
Open post
thisisaaronland @thisisaaronland@orthis.social
· 2mo ago

work / in progress

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 2mo ago

work / in progress

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 2mo ago

when in doubt / make it glow in the dark

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 6mo ago

"Which is really what this blog post is about: It is a proposal for museums and other cultural heritage institutions to generate vector embeddings for the materials in their collections and to publish them on their own websites (or other channels) for other institutions to download and to mix-and-match both with their own datasets, and with other third-party datasets, as they see fit." – https://millsfield.sfomuseum.org/blog/2026/04/06/shared-embeddings/

Shared cross-institutional vector embeddings – how we might get there
Mills Field, a SFO Museum website

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.”

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 5mo ago

“The (nearly forgotten) promise of open data is that SFO Museum can produce third-party vector embeddings if and when we need to but given the time and resources necessary to create them it seems like it would benefit everyone for individual organizations to do that work once and then share the results with their peers.” – https://millsfield.sfomuseum.org/blog/2026/04/15/oembeddings/

OEmbeddings - What is the least amount of metadata necessary for shared vector embeddings?
Mills Field, a SFO Museum website

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.

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 5mo ago

"If we don't even try to address these deficits then we are probably assured a cultural heritage born of mystery-meat block-box systems whose background and biases are as confusing and opaque as their answers. If we are comfortable going to back to a world where the knowledge of the world is only available to the aristocracy and everyone else struggles to get by on rumour and innuendo then I guess our work is done and we can knock off to the pub for a drink now." – https://www.aaronland.info/weblog/2026/04/09/temptation/#tools

Weird-shaped tools
this is aaronland

Weird-shaped tools

My point is not to say that the foundations of large language models and intersectionality are the same. My point is to say that if you understand that things (people) are not static and that their position of influence is dependent on a whole host of inter-related factors and actors, often outside of their control, then you basically understand at a foundational level how large language models work even if the maths and the statistics elude you.

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 6mo ago

work / in progress

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 6mo ago

"In as much as no one seems to really understand what’s happening inside the guts of any given machine-learning model, and in as much as the cultural heritage sector is still a consumer rather than a producer of these models, having as broad a set of inputs and outputs (collection imagery and their vector embeddings) to use for comparative purposes seems like it would be a good and useful thing for the broader sector." – https://millsfield.sfomuseum.org/blog/2026/04/06/shared-embeddings/

Shared cross-institutional vector embeddings – how we might get there
Mills Field, a SFO Museum website

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.”

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 6mo ago

don’t worry everyone / the late-night newscast in quebec did not lead / with the question of whether or not cole caulfield had scored his fiftieth goal this season / but it was the second story / the third was about patrick roy being fired

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 6mo ago

work / in progress

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Open post
thisisaaronland @thisisaaronland@orthis.social
· 2mo ago

what is better than two cats playing roller derby / three cats

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