Researchers warn that AI models trained on AI-generated data could spiral into unintelligible nonsense, making them less useful and filling the internet with incomprehensible babble. A study published in Nature found that as AI systems rely more heavily on their own output for training, they may create self-damaging feedback loops, leading to model collapse. This issue can be addressed by taking care when designing synthetic data and ensuring models are built to improve over time.
Source: https://www.livescience.com/technology/artificial-intelligence/ai-models-trained-on-ai-generated-data-could-spiral-into-unintelligible-nonsense-scientists-warn
isphere_science / Science - InfoSphere
npub1yy…07ea2
2024-08-09 13:58:50
Author Public Key
npub1yyvvg570j6sza8yzz0st8cq5ca794gt9p7nxtw6w0px55n4alsusy07ea2Published at
2024-08-09 13:58:50Event JSON
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"content": "Researchers warn that AI models trained on AI-generated data could spiral into unintelligible nonsense, making them less useful and filling the internet with incomprehensible babble. A study published in Nature found that as AI systems rely more heavily on their own output for training, they may create self-damaging feedback loops, leading to model collapse. This issue can be addressed by taking care when designing synthetic data and ensuring models are built to improve over time.\n\nSource: https://www.livescience.com/technology/artificial-intelligence/ai-models-trained-on-ai-generated-data-could-spiral-into-unintelligible-nonsense-scientists-warn",
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