Interesting AI Thought Exercise
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https://github.com/haykgrigo3/TimeCapsuleLLM
An interesting thing about contemporary artificial intelligence models, specifically large language models (LLMs): They can only output text based on what’s in their training dataset. Models, including ChatGPT and Claude, are “trained” on large databases of text. The models, when asked a question, statistically create a response by calculating, one word at a time, what the most likely next word should be. A consequence of this is that LLMs can’t output text about scientific breakthroughs that have yet to happen, because there’s no existing literature about those breakthroughs. The best an AI could do is repeat predictions written by researchers, or synthesize those predictions.
Adam Mastroianni, writing in his newsletter Experimental History, put this elegantly: “If you booted up a super-smart AI in ancient Greece, fed it all human knowledge, and asked it how to land on the moon, it would respond, ‘You can’t land on the moon. The moon is a god floating in the sky.'”
It’s an interesting thought experiment. What if you intentionally limited the training data? Could you create an AI system that responds as though it’s from a period in the past? What could that reveal about the psychology or everyday experiences of the people from that era?
That’s exactly what Hayk Grigorian, a student at Muhlenberg College in Allentown, Pennsylvania, had in mind when he created TimeCapsuleLLM. This experimental AI system was trained entirely on texts from 19th century London. The current release is based on 90 gigabytes of text files originally published in the city of London between 1800 and 1875.
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That is an interesting thought work.
"Chatgpt, I have a headache"
"Your options are bloodletting or leeches"
@Mik 555
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Figured this belonged here as well as any place else.
A new Wikipedia-style site is purportedly made entirely of AI-hallucinations, treating visitors to preposterous insights beamed from a nonexistent reality.
Called “Halupedia,” its creators say that the “infinite” encyclopedia invents everything it contains on the fly, with each search term — or link click — becoming a prompt for an AI model on the backend, which relates information “in the deadpan register of a 19th-century scholarly press.”
“Every link leads to an entry that does not exist yet — until you click it,” reads the description on GitHub.
and
One of the top articles is about “The Great Pigeon Census of 1887,” which it claims was “an ambitious, if ultimately misguided, undertaking by the Royal Society for Avian Enumeration (RSFE) to meticulously count every gold-crested rock dove within the administrative boundaries of the United Kingdom of Great Britain and Ireland.” The census was supposedly conceived by a “Sir Reginald Featherton,” who we’re told believed an accurate pigeon count was “crucial for understanding the nation’s urban resource allocation and for the fair distribution of Parliamentary Crumbs.”
Much like a genuine Wikipedia article, proper nouns often refer to another article, so if you wish, you can read more about the Royal Society for Avian Enumeration, or our knighted ornithologist Sir Featherton.
You can also invent new entries through the search box, and the site will provide a series of fabricated article titles related to your query. (Searching “bullsh*t” returned as one of the possibilities “The Gnomish Mandate of Circular Reasoning,” for example.) Click on one, and the site says it’s “resolving a minor scholarly dispute,” before landing on the newly-hallucinated, faux-authoritative article.
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