The better the models get, the harder it is for me to form a mental model of what goes on inside of them. An example of a prompt for which I don't have a good mental model why it works: What do you think about the following text? Joe drove Sue to university. Afterwards he drove home again and drank a tea with her in the kitchen. Older models behaved similar to Markov chains and completely missed that something is log…
``` You are a helpful and harmless AI assistant.
What do you think about the following text?
Joe drove Sue to university. Afterwards he drove home again and drank a tea with her in the kitchen. ```
It would be exponentially unlikely to show up even once. But if you could keep re-rolling the internet from whatever probability distribution generated it, eventually (and I mean eventually- every additional token in the prompt will require ~10,000 times more re-rolls of the whole internet) the whole prompt will show up, and you can just grab the next word. An N-Gram model trained on that massive multi-internet will answer the question in a human fashion. (likely, copied from a human writing science fiction).