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History LLMs: Models trained exclusively on pre-1913 texts

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Re: History LLMs: Models trained exclusively on pre-1913 texts

#11
post #3

“Time-locked models don't roleplay; they embody their training data. Ranke-4B-1913 doesn't know about WWI because WWI hasn't happened in its textual universe. It can be surprised by your questions in ways modern LLMs cannot.” “Modern LLMs suffer from hindsight contamination. GPT-5 knows how the story ends—WWI, the League's failure, the Spanish flu.” This is really fascinating. As someone who reads a lot of history an…

This is definitely fascinating - being able to do AI brain surgery, and selectively tuning its knowledge and priors, you'd be able to create awesome and terrifying simulations.

Re: History LLMs: Models trained exclusively on pre-1913 texts

#13
post #3

“Time-locked models don't roleplay; they embody their training data. Ranke-4B-1913 doesn't know about WWI because WWI hasn't happened in its textual universe. It can be surprised by your questions in ways modern LLMs cannot.” “Modern LLMs suffer from hindsight contamination. GPT-5 knows how the story ends—WWI, the League's failure, the Spanish flu.” This is really fascinating. As someone who reads a lot of history an…

"...what do you mean, 'World War One?'"

Re: History LLMs: Models trained exclusively on pre-1913 texts

#14
post #4

The sample responses given are fascinating. It seems more difficult than normal to even tell that they were generated by an LLM, since most of us (terminally online) people have been training our brains' AI-generated text detection on output from models trained with a recent cutoff date. Some of the sample responses seem so unlike anything an LLM would say, obviously due to its apparent beliefs on certain concepts, t…

I used to teach 19th-century history, and the responses definitely sound like a Victorian-era writer. And they of course sound like writing (books and periodicals etc) rather than "chat": as other responders allude to, the fine-tuning or RL process for making them good at conversation was presumably quite different from what is used for most chatbots, and they're leaning very heavily into the pre-training texts. We don't have any living Victorians to RLHF on: we just have what they wrote.

To go a little deeper on the idea of 19th-century "chat": I did a PhD on this period and yet I would be hard-pushed to tell you what actual 19th-century conversations were like. There are plenty of literary depictions of conversation from the 19th century of presumably varying levels of accuracy, but we don't really have great direct historical sources of everyday human conversations until sound recording technology got good in the 20th century. Even good 19th-century transcripts of actual human speech tend to be from formal things like court testimony or parliamentary speeches, not everyday interactions. The vast majority of human communication in the premodern past was the spoken word, and it's almost all invisible in the historical sources.

Anyway, this is a really interesting project, and I'm looking forward to trying the models out myself!

Re: History LLMs: Models trained exclusively on pre-1913 texts

#15
post #3

“Time-locked models don't roleplay; they embody their training data. Ranke-4B-1913 doesn't know about WWI because WWI hasn't happened in its textual universe. It can be surprised by your questions in ways modern LLMs cannot.” “Modern LLMs suffer from hindsight contamination. GPT-5 knows how the story ends—WWI, the League's failure, the Spanish flu.” This is really fascinating. As someone who reads a lot of history an…

When you put it that way it reminds me of the Severn/Keats character in the Hyperion Cantos. Far-future AIs reconstruct historical figures from their writings in an attempt to gain philosophical insights.

Re: History LLMs: Models trained exclusively on pre-1913 texts

#16
post #8

I’d like to know how they chat-tuned it. Getting the base model is one thing, did they also make a bunch of conversations for SFT and if so how was it done? We develop chatbots while minimizing interference with the normative judgments acquired during pretraining (“uncontaminated bootstrapping”). So they are chat tuning, I wonder what “minimizing interference with normative judgements” really amounts to and how objec…

They have some more details at https://github.com/DGoettlich/history-llms/blob/main/ranke-4...

Basically using GPT-5 and being careful

Re: History LLMs: Models trained exclusively on pre-1913 texts

#19
post #8

I’d like to know how they chat-tuned it. Getting the base model is one thing, did they also make a bunch of conversations for SFT and if so how was it done? We develop chatbots while minimizing interference with the normative judgments acquired during pretraining (“uncontaminated bootstrapping”). So they are chat tuning, I wonder what “minimizing interference with normative judgements” really amounts to and how objec…

You could extract quoted speech from the data (especially in Q&A format) and treat that as "chat" that the model should learn from.

Re: History LLMs: Models trained exclusively on pre-1913 texts

#20
The knowledge machine question is fascinating ("Imagine you had access to a machine embodying all the collective knowledge of your ancestors. What would you ask it?") – it truly does not know about computers, has no concept of its own substrate. But a knowledge machine is still comprehensible to it.

It makes me think of the Book Of Ember, the possibility of chopping things out very deliberately. Maybe creating something that could wonder at its own existence, discovering well beyond what it could know. And then of course forgetting it immediately, which is also a well-worn trope in speculative fiction.

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