AI models face collapse if they overdose on their own output

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Recursive training leads to nonsense, study finds

Researchers have found that the buildup of AI-generated content on the web is set to"collapse" machine learning models unless the industry can mitigate the risks.

"Long-term poisoning attacks on language models are not new," the paper says."For example, we saw the creation of click, content and troll farms, a form of human 'language models' whose job is to misguide social networks and search algorithms. The negative effect that these poisoning attacks had on search results led to changes in search algorithms.

"If subsequent models are trained on an AI-generated data set that over-represents Golden Retrievers, the problem is compounded. With enough cycles of over-represented Golden Retriever, the model will forget that obscure dog breeds such as Petit Basset Griffon Vendéen exist and generate pictures of just Golden Retrievers. Eventually, the model will collapse, rendering it unable to generate meaningful content.

 

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