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AI Models Face Collapse If They Overdose On Their Own Output
According to a new study published in Nature, researchers found that training AI models using AI-generated datasets can lead to "model collapse," where models produce increasingly nonsensical outputs over generations. "In one example, a model started with a text about European architecture in the Mi...
"In one example, a model started with a text about European architecture in the Middle Ages and ended up -- in the ninth generation -- spouting nonsense about jackrabbits," writes The Register's Lindsay Clark. In an accompanying article, Emily Wenger, assistant professor of electrical and computer engineering at Duke University, illustrated model collapse with the example of a system tasked with generating images of dogs. While she concedes an over-representation of Golden Retrievers may be no bad thing, the process of collapse is a serious problem for meaningful representative output that includes less-common ideas and ways of writing.
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