Part 3/11:
Researchers have identified a phenomenon known as neural scaling laws, which illustrate a proportional relationship between model performance and training data size. As models become larger and more capable, they exhibit improved performance, minimizing training loss and generating novel behaviors — an outcome understood as emergence. However, the reasons behind emergence remain largely elusive within the scientific community, prompting researchers to investigate whether it might be linked to compositional generalization—the capability to synthesize language skills into coherent structures.