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How Quickly Do Large Language Models Learn Unexpected Skills?

A new study suggests that so-called emergent abilities actually develop gradually and predictably, depending on how you measure them. The post How Quickly Do Large Language Models Learn Unexpected Skills? appeared first on Nautilus.

Two years ago, in a project called the Beyond the Imitation Game benchmark, or BIG-bench, 450 researchers compiled a list of 204 tasks designed to test the capabilities of large language models, which power chatbots like ChatGPT. On most tasks, performance improved predictably and smoothly as the models scaled up—the larger the model, the better it got. But with other tasks, the jump in ability wasn’t smooth. The performance remained near zero for a while, then performance jumped. Other studies found similar leaps in ability.

The authors described this as “breakthrough” behavior; other researchers have likened it to a phase transition in physics, like when liquid water freezes into ice. In  published in August 2022, researchers noted,” a word that describes collective behaviors that only appear once a system reaches a high level of complexity.

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