can you divide this text in relevant part please: not sure where to ask about this sort of thing, but is there any research on what happens if you pre-train a model (LLM like or otherwise) on massive amounts of generated data (like valid board game moves, arithmetic/multiplication, encoding/decoding, simulated data, etc.) and THEN train it on language or something else? would there be any useful amount of transfer learning, or would it make it easier for the model to learn the new data or something else?