AI model collapse refers to the deterioration of generative models' output quality due to their training on previous, often flawed, versions of themselves.
As AI becomes integral across sectors, the potential degradation of its quality raises concerns about the reliability of AI tools for businesses and consumers alike.
Training models on AI-generated data leads to compounded errors, as inaccuracies are perpetuated through a cycle of self-reliance, casting doubt on AI’s future efficacy.
Once the internet is saturated with low-quality AI content, future AI models may lose their robustness, affecting everything from customer satisfaction to bias understanding.
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