Ai World AI World Journal Report: π The Great Autopoiesis: AI Reshapes Intelligence
π The Great Autopoiesis: AI Reshapes Intelligence 1 source The provided text from the AI World Journal discusses the significant shift in how artificial intelligence, particularly large language models (LLMs), are trained. Initially relying on vast amounts of human-generated data, AI development has transitioned to an autopoietic system where AI itself generates the data for training new models. This change is driven by the scarcity of high-quality human text and involves techniques like synthetic data expansion, model distillation, and the feedback loop of AI-mediated interactions. While this self-referential process accelerates AI capabilities, it also introduces substantial risks such as amplification of errors, homogenization of language, erosion of authenticity and provenance, and potential model degradation. The article emphasizes the crucial need for a hybrid approach that balances AI-generated data with a preserved human data anchor and robust safeguards to ensure the continued relevance and diversity of intelligence.