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Tired of your AI chatbot’s constantly-glazing therapy-speak? You could instead try striking up a conversation with “Talkie,” an old-timey AI model which is trained purely on books, newspapers, and other text sources from before the year 1930.
With its thirteen billion parameters, the researchers behind Talkie say it’s the largest “vintage” model they’re aware of, capable of holding down a conversation as if truly stuck in a past when movies with sound in them were still a novel phenomenon, and when news announcers rattled off the latest signs of tumult in the world in a bouncy Mid-Atlantic accent.
Intriguingly, Talkie is “basically” unaware of the fact it’s limited to pre-1930 times, according to David Duvenaud, an associate professor of computer science at the University of Toronto. The AI, he explained in a tweet, “doesn’t have a system prompt and they’re not smart enough yet (as far as we can tell) to introspect well enough to figure out their cut-off date.”
Announcing Talkie: a new, open-weight historical LLM! We trained and finetuned a 13B model on a newly-curated dataset of only pre-1930 data. Try it below!
with @AlecRad and @status_effects 🧵 pic.twitter.com/kThUESG13e — David Duvenaud (@DavidDuvenaud) April 27, 2026
Talkie isn’t perfect. The researchers note that it exhibits signs of “temporal leakage,” in which it produces clearly anachronistic answers, such as knowing that “Franklin D. Roosevelt was president of the United States from 1933 to 1937.” This shows the difficult of keeping its data set pure.
Nonetheless, it raises fascinating questions. What is an LLM’s ability to predict the future? Can the nearly-century-old AI learn a modern programming language? Better yet, can it make scientific discoveries?
“As Demis Hassabis has asked,” the researchers wrote in a blog post, referring to the Google DeepMind CEO, “could a model trained up to 1911 independently discover General Relativity, as Einstein did in 1915?”
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