New research published in Nature has highlighted the risks associated with using synthetic data to train artificial intelligence (AI) models. The study identified that the use of synthetic data can lead to the rapid degradation of AI models. The researchers found that AI models tend to collapse over time due to the accumulation and amplification of mistakes from successive generations of training. This deterioration is linked to the design of the model, the learning process, and the quality of data used. The study also raises concerns about the over-representation of majority subpopulations at the expense of minority groups in the early stages of collapse, leading to nonsensical outputs.
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