To make this kind of research accessible, I’m open-sourcing the workflow I created for this investigation as a small toolkit, Antiquity, enabling anyone with a question and a coding agent to conduct similar historical archival investigations.

https://github.com/jessewaites/antiquity

I also liked the aesthetics of it and the little effects (meteorite and volcano, but please fix the rhino and the text flowing around it while it rotates).

I wonder what else could be found in such archives. Some ideas: - Locations or routes of sunken ships and their missing cargo?

- Some pirate stories, maybe about a now-forgotten but once-legendary pirate captain?

- Unusual weather events, like snow in the summer?

(edit: formatting)

Makes me wonder how much the author himself learned about the Dutch East India Company. I suspect very little, if anything. Something about these exercises reminds me of junk food: empty calories and all that...

I'm working on a similar project for contemporary political opinion media. Every podcast, blog, oped, or show cut into little pieces with the structure, speaker, quotes and nouns pulled out and cross-referenced. I bring it up because I wonder if this kind of heavy-weight preprocessing is worth bringing to historical documents as well. It would be much more expensive, initially, but afterwards allows questions get answered even cheaper than they are in your current system. It may be worth collecting interested parties and co-investing in the structured parsing.

Also modern transcription and historical document scanning have a similar shaped problem - dealing with misspelled words and trying to infer their corrections from context.

Using Opus 5.5 to discover a new eyewitness record of the dodo - https://smackernews.com/item/49926917 HN - Oct 2026 (79 comments)

Many people don’t notice, but even Wikipedia has no normalization between articles in different languages. The language button there acts like its showing you a translated version of the article but its actually a completely different Encyclopedia and community of editors with no cross reference to the other language’s article and references at all. Articles that are stubs on the English page may be massive fully fleshed out articles in another language, and nothing native to the site or anything I’ve seen will tell you that there is more information in one variant

LLM’s can find the word associations and compare them in all languages, even if it itself doesn't innately know language

and there would be so much low hanging fruit here like this engineer found

I asked the ChatGPT (I think it was 5.6 medium?) to look at old paintings or sculptures that might contain previously overlooked health issues in the subject.

One of the more famous examples of this is that "Mona Lisa" likely had hypercholesterolemia. The evidence in that case is that da Vinci painted her with a xanthelasma (cholesterol deposit) on her eyelid and a putative lipoma on her right hand.

GPT churned for a few minutes and suggested that the old man in Gustav Klimt's "Portrait of an old man in profile" might have had Frank's sign (a crease on the ear-lobe correlated w/ coronary artery disease: https://onlinecollection.leopoldmuseum.org/en/object/4325-po...).

I told it that the painting was so abstract that I was unconvinced.

It "agreed" and churned a little more and it suggested that the subject in J.A. van Ravesteyn's "Portrait of a Gentleman" (1624) had a clearer sign of Frank's sign that hadn't been previously noted.

I think that one is a little more compelling (https://www.proantic.com/en/1299214-jan-van-ravesteyn-presum...).

For the record, I think this project was an excellent presentation, I loved the interactive elements snd the meteorite (or is that a meteorwrong?) to come across the page. This is about as good of a use of LLM's as I have seen. I didn't see anything about it in the article, but does anyone know what future plans are for this particular project, or is that a wrap? I didn't see I the Where This Stands section anything about future search topics. This really feels like a time where finding the question is every bit as important as finding an answer to that question.

https://github.com/jsoeterbroek/duinroos_replica_goldhat/tre... on Github.

But Here, the start is "What field should I approach and what questions should I ask?"

But this is NOT the same!

When I watch my non-tech friends vibe-coding, I'm struck by how they are so ignorant of basic tech stuff, but little tiny bubbles of "experience" start to percolate in them after a while. Things like "wait, I think this project has weird dependencies that are going to cause trouble when I move it to my office machine" or "hold on, the mobile version doesn't share the same text with the desktop version?"

It is much less interesting to have an attitude of "I don't know or care, just give me a 'result'" vs "Aha! I see where we could apply this in a productive way!"

This is like the Anthropic people feeling like they found many many "very important" Linux bugs https://www.youtube.com/watch?v=NnV_cWeoo5Q - hint: no.

When it's something you know about, the overstating is obvious! It's only when you don't know about things that shallow work (or slop) feels significant.

Finding something in archives is definitely one of those.