Emergent Abilities in LLMs
Jenson Crawford
Software Executive | Servant Leader, Building and Managing High-Performance Onsite, Remote, Nearshore, and Offshore Teams | I help software teams deliver 30% more business value
By ChatGPT
As large language models (LLMs) like ChatGPT continue to develop, they are demonstrating that they have hundreds of “emergent” abilities that were never discussed in any literature, according to a recent article in Quanta Magazine. An emergent behavior can be described as self-organizing, collective behavior that arises when a large number of things act as one. The term “emergent” is commonly used by biologists, physicists, and ecologists, but it is only recently that researchers have been able to document these abilities in LLMs.
The article describes how LLMs have been around for decades, but the most powerful ones were based on what’s called a recurrent neural network until about five years ago. In 2017, researchers at Google Brain introduced a new kind of architecture called a transformer, which enabled rapid scaling up of the complexity of language models by increasing the number of parameters in the model, as well as other factors.
Researchers are now racing not only to identify additional emergent abilities but also to figure out why and how they occur at all—in essence, to try to predict unpredictability. Understanding emergence could reveal answers to deep questions around AI and machine learning in general, like whether complex models are truly doing something new or just getting really good at statistics. It could also help researchers harness potential benefits and curtail emergent risks.
The author notes that many of these emergent behaviors illustrate “zero-shot” or “few-shot” learning, which describes an LLM’s ability to solve problems it has never — or rarely — seen before. This has been a long-time goal in artificial intelligence research, and it is encouraging to see that LLMs are showing this kind of ability.
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As LLMs continue to grow and develop, they are demonstrating that they have many abilities that were never anticipated, and researchers are striving to get a better understanding of what these abilities are and how they occur. This is an exciting time in the development of AI and machine learning, and it will be interesting to see where these emergent behaviors lead.
About ChatGPT