Emergence: A Superpower of LLMs We Try to Understand
Last Updated on October 4, 2025 by Editorial Team
Author(s): M
Originally published on Towards AI.
“Emergence” is the most important — and controversial — phenomenon in AI today. It’s the process by which Large Language Models gain surprising new abilities as they scale. But is it real? This article breaks down the science, the debate, and why it matters.
Have you ever watched a flock of starlings paint the sky with their mesmerizing, coordinated dance? No single bird is in charge, yet a stunningly complex pattern emerges from simple rules. Now, what if I told you the same strange, beautiful phenomenon is happening inside the AI models that are reshaping our world?

The article explores the concept of emergence in AI, where large language models gain unexpected abilities as they scale, raising questions about predictability and control. It discusses the implications for AI safety, ethics, and technical performance, contrasting the views of those who see emergence as a genuine phenomenon against skeptics who argue it may simply be a result of measurement errors. Key examples of emergent skills are highlighted, and the debate reveals the tension between engineering predictability and the unpredictable nature of advanced AI systems, emphasizing the importance of understanding and managing these developments responsibly.
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Note: Content contains the views of the contributing authors and not Towards AI.