Is ChatGPT an N-gram model on steroids?

This podcast episode delves into the intricate behavior of transformers, unpacking the significance of template matching and the interplay between syntax and semantics, while also introducing innovative methods to detect overfitting. The discussion emphasizes that while transformers exhibit impressive predictive capabilities through statistical descriptions, they may lack a fundamental understanding of language akin to human semantics. The episode further explores curriculum learning, illustrating how transformers evolve from simple to complex rules during training, and wraps up with a forward-looking perspective on the need for deeper explanations of transformer mechanisms, paving the way for future research in this rapidly evolving field.