Synthetic data risks ‘model collapse’ but may spur renewed interest in robotics
First, we learn that generative AI models can “hallucinate”, an elegant way of saying that large language models make stuff up. As ChatGPT itself informed me , LLMs can generate fake historical events, non-existent people, false scientific theories and imaginary books and articles. Now, researchers tell us that some LLMs might collapse under the weight of their own imperfections.
Indeed, researchers say there may be a first-mover advantage for early LLMs trained on unpolluted data that is now unavailable to next-generation models. Logic suggests that this will also increase the value of fresh, private, human-generated data — publishers take note. The theoretical dangers of model collapse have been discussed for years and researchers still argue that the discriminate use of synthetic data can be invaluable.
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