the rapid growth of data used to train Large Language Models (LLMs), particularly Meta's LLM. It argues that this expansion is fueled by the inclusion of synthetic data, which is data generated by the LLMs themselves, leading to a cycle of data consumption and regeneration. This process is likened to "synthetic cannibalism," as the LLM consumes its own outputs, and to "incestuous phylogeny," as the model's development is influenced by its own past outputs. The text suggests that this trend could lead to the creation of a self-sustaining synthetic entity, with consequences that may be both beneficial and alarming.

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