Part 12/16:
Advances in computational power and data availability led to more sophisticated models, using larger contexts and attention mechanisms—tools that weigh the importance of different previous words. These ideas underpin modern large language models like GPT, which generate coherent text by predicting the next token based on a vast context.
However, as these models produce more realistic language, concerns grow about feedback loops where models learn from and mirror existing internet content. This may cause models to become stale, repeating patterns rather than generating genuinely novel ideas.