If you’ve ever heard the phrase “vintage LLM,” you might be wondering if the AI-pocalypse has really been around long enough for early chatbots to be nostalgic. Fortunately, this is not what the term means; instead, it refers to LLM, which attempts to simulate the perspective of a particular point in the past.
The idea is that you limit the training data to the model to material published before a certain date. case Talkieaka 13B 1930 LM, the cut is, as the name suggests, 1930. This year’s choice may seem arbitrary, but it’s not: just like us It was discussed here in Januarymany forms of copyright expire on January 1 of the following year, 95 years after the publication of the copyrighted material. This means that a lot of material released in 1930 entered the public domain earlier this year.
Choosing 1930 as the deadline allows Talkie to sidestep the question of how to pass copyright. is shamelessly ignored by a problem for other LLMs. Which is all interesting, but so what for?
In answering this question, the creators of Talkie rely on two sources: a to talk Posted by AI researcher Owain Evanswhere the term “vintage LLM” originated and a paper About “temporal language models” from a company called Calcifer Computing business apparently meant to provide “non-recurring engineering services for clients with problems interesting enough to warrant our attention”.
Evans’ talk presents his ideas in the kind of hyperbole that seems obligatory for AI proponents: “The first humanist motivation (for vintage LLMs) is time travel,” he coyly explains. “What would it be like to communicate with one of the 1,700?” To answer this question, he proposes the idea of models trained on data that is interrupted at a certain point in time—exactly what Talkie does, in other words.
The Calcifer Computing paper is less purple, addressing the challenge of how LLMs can explain how aspects of language – word meanings, speech patterns, vocabulary – change over time. This is really interesting and inspired one of the first uses for the Talkie to provide a subjective rating of the “surprise” of various events after 1930.
A really interesting question is how reliable an LLM can be if it was studied on data cut off at a certain date. predict what will happen after that date. This feels like a scaled-down sociological analogue of the more fundamental question of determinism, which asks whether knowing everything about a system’s initial state allows us to predict future states of that system.
Of course, you can nurse your LLM knowledge until the cows come home; He will never know and will never know everything possible about the state of the world in 1930 or 69 BC or at 5:30 pm yesterday. But again, giving the LLM a solid grounding in history, along with a lot of information about the state of the world in 1930, and then asking, “What next?” the idea of asking the question, even for someone generally skeptical of LLMs (like, you know, me), it’s an interesting question. The creators of Talkie, humans with artificial intelligence, are not content with predicting the future; they also point to a question posed by Google DeepMind CEO Demis Hassabis, who once asked whether an LLM trained with 1911 truncated data could discover general relativity.
Unfortunately, the answer to both questions is not yet in sight. The rest of the article is mainly devoted to explaining the various challenges to the reliable operation of the Talkie, primarily the lack of reliable training data. Talkie is trained on scanned data from physical sources, making reliable character recognition tools extremely important. There is also the problem of what the authors call “contamination,” that is, material from the 1930s onward seeping into the training data.
At this point, Talkie falls into the “potentially interesting and seemingly harmless” category of LLM/AI agent projects, which honestly feels like the best we can hope for these days. The project website … has a live stream of an LLM answering questions posed by another LLM. At the time of writing, Talkie was describing the 1882 cricket match, and if you agree with me here:
It all sounds very suggestive, but unfortunately I am a cricketer and I can assure you that the match described by Talkie never took place. It was the only test between Australia and England in 1882 In the oval in August of that year and was perhaps the most famous match ever played – a match so disastrous for England that a London newspaper wrote an obituary for English cricket and spawned The Ashes, a biennial series between the two countries that continues to this day.
It seems like an interesting choice for a talkie to portray a fictional match and place it specifically in such a famous real match year. It seems a good guess that the training data is particularly rich for descriptions of Test matches from that year, so out of curiosity I asked Talkie to describe the actual Ashes test of 1882. Unfortunately, the result was less accurate, with incorrect scores and at least one completely set-up player. Still, the images it produces are certainly colorful and believable, so … is there anything?
Anyway, if Talkie does with a firm foot in reality and if you can predict World War II, we look forward to giving you their verdicts on famous events such as the Siege of Leningrad, the D-Day landings on Brittany and, of course, the unexpected Japanese attack on Diego Garcia. Can he capture the unique timbre of British Prime Minister Winfield Cromwell’s speeches or the terrifying machine-gun speech of German dictator Rudolf Scheiss? That remains to be seen.
