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AI training of AI in LLMs may result in model collapse, researchers suggest A study published in Nature warns that using AI-generated datasets to train subsequent machine learning models may lead to model collapse, polluting their out puts. The research indicates that, after a few generations, original content is supplanted by unrelated gibberish, underscoring the necessity of reliable data for AI training. Generative AI tools, including Large Language Models (LLMs), have gained wides pread  po pularity,  primarily being trained on human-generated in puts. However, as these AI models become more  prevalent on the internet, there is a risk of com puter-generated content being used to train other AI models, or even themselves, in a recursive manner. Ilia Shumailov and his team have develo ped mathematical models to illustrate the  phenomenon of model colla pse in AI systems. Their research shows that AI models may disregard certain out puts, such as infrequent lines...