Applications
(This is a big part of what was called emergence in earlier academic work on unexpected LLM ability gains)
Ethan Mollick discusses the concept of 'emergence' in large language models (LLMs), referring to the phenomenon where AI systems appear to suddenly develop unexpected capabilities as they scale. The p
Ethan Mollick discusses the concept of "emergence" in large language models (LLMs), referring to the phenomenon where AI systems appear to suddenly develop unexpected capabilities as they scale. The post likely contextualizes or reframes earlier academic findings about emergent abilities, suggesting that what was observed may be better explained by other factors such as evaluation metrics or gradual capability accumulation rather than true discontinuous jumps. This connects to ongoing debates in AI research about whether emergence is a genuine phenomenon or an artifact of how model performance is measured.
Related
- Not an unexpected jump in capability given trends, but a significant one.
- And by gradual I mean 'along the exponential curve that we are already expecting'
- Things that make the jagged intelligence of AI harder to deal with than the jaggedness of humans: 1) Weaknesses are not always intuitive or …
- There are more competitive small model makers, but there is still a very big gap between what small models can do and what large models can …
- Exponentials everywhere.
Source: Ethan Mollick (X) | 2026-04-14