AI Definitions: Model Collapse

AI Model Collapse - The idea that AI can eat itself by running out of fresh data, so that it begins to train on it’s on product or the product of another AI. This would magnify errors and bias and make rare data more likely to be lost, leading to an erosion of diversity—not only ethnic diversity but linguistic diversity as the AI model’s vocabulary shrinks and its grammatical structure becomes less varied. In effect, the model becomes poisoned with its own projection of reality. A.I.-generated data is often a poor substitute for the real thing. Example

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