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As an exercise so I could learn the technology, I trained a model exclusively on the Public Domain works of L Frank Baum, specifically the "Wonderful Wizard of Oz" series (did you know there are 14 books in the series just by Baum?!). The model created is not useful as a tool, and more often than not just produces English gibberish, but every now and then it can produce original coherent statements.
Again, I didn't do this to produce a useful tool, but rather an exercise to learn how to build models.
However, this means I can refute your statement because 100% of the input data is public domain novels. Also, I trained it on my own hardware powered 100% by solar power.
So we created multitudes of digital byte-sized monkeys...and gave them m/billions of typewriters. . . :p
You're not far off from describing primative LLMs. In fact, the recent innovation in the last 5 years was the application of a specific technique published in a paper called "Attention Is All You Need" that the secret sauce is "attention" added via a transformer layer. This concept is what made GPT, Claude, etc the life-like responses they have today.
Super cool! Thanks for sharing :D
...and for making me feel like that cool kid in class whose silly quip is leveraged by the teacher to expand context for everyone. 😎
Cool that you did that. However, "Large" as in "Large Language Model" generally refers to the dataset size, and 14 books is not Large.