Why do LLMs have emergent properties?

The article explores the concept of emergent properties in large language models (LLMs), which become capable of performing tasks as their parameter count increases. It argues that this phenomenon, akin to natural occurrences like phase changes, should not surprise us as similar behaviors are evident across various machine learning and algorithmic environments. The discussion suggests the difficulty in predicting when and how new capabilities will emerge, using examples from nature and tech to illustrate the notion of emergence as a common occurrence.

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