Part 6/11:
The prevailing narrative has been "bigger is better." Yet, simply increasing parameters or training data has diminishing returns, especially when models already have access to vast amounts of text. GPT-3 was trained on the equivalent of 200 lifetimes’ worth of data, and doubling that isn’t guaranteed to produce a leap in intelligence. Instead, further progress likely depends on breakthroughs in cognitive architecture—how models process, store, and generalize knowledge—rather than just scaling up.