Introduction to AI Language Models
A hobbyist developer, who is also a computer science student, has been working on a project to build AI language models that speak Victorian-era English. The goal of this project is to create an AI model that can capture the authentic voice of the Victorian era. The developer, Hayk Grigorian, has been training his AI model, called TimeCapsuleLLM, on texts from 1800-1875 London.
How TimeCapsuleLLM Works
TimeCapsuleLLM is a small AI language model that has been trained entirely on texts from 1800-1875 London. The model is designed to generate text that is heavy with biblical references and period-appropriate rhetorical excess, giving it an authentic Victorian voice. Grigorian has been testing his model by prompting it with different phrases and seeing how it responds. One of the most intriguing outputs came when he prompted the model with "It was the year of our Lord 1834."
A Glimpse into the Past
The model generated a response that mentioned real protests from 1834 London, including the involvement of Lord Palmerston. Grigorian was curious about the accuracy of the model’s output, so he did some fact-checking. He discovered that the protests mentioned by the model actually did occur in 1834 London, and that Lord Palmerston’s actions had played a role in the protests. This was a surprising discovery for Grigorian, who had not known about the protests before.
Historical Large Language Models
TimeCapsuleLLM is part of a growing field of research into Historical Large Language Models (HLLMs). These models are trained on large datasets of historical texts and can be used to generate text that is similar in style and tone to the original texts. Other examples of HLLMs include MonadGPT, which was trained on 11,000 texts from 1400 to 1700 CE, and XunziALLM, which generates classical Chinese poetry following ancient formal rules. These models offer researchers a chance to interact with the linguistic patterns and thought processes of past eras.
Conclusion
The development of TimeCapsuleLLM and other HLLMs is an exciting area of research that can help us learn more about the past and how people thought and communicated. These models have the potential to be used in a variety of applications, from education to entertainment. As Grigorian’s experience shows, they can also lead to unexpected discoveries and a deeper understanding of historical events.
FAQs
- What is TimeCapsuleLLM?
TimeCapsuleLLM is a small AI language model that has been trained on texts from 1800-1875 London to capture the authentic voice of the Victorian era. - What is the goal of Historical Large Language Models?
The goal of HLLMs is to generate text that is similar in style and tone to historical texts, and to offer researchers a chance to interact with the linguistic patterns and thought processes of past eras. - How does TimeCapsuleLLM work?
TimeCapsuleLLM is trained on a dataset of texts from 1800-1875 London and uses this training to generate text that is heavy with biblical references and period-appropriate rhetorical excess. - What was the surprising discovery made by Hayk Grigorian?
Grigorian discovered that the protests mentioned by TimeCapsuleLLM in response to the prompt "It was the year of our Lord 1834" actually did occur in 1834 London, and that Lord Palmerston’s actions had played a role in the protests.
