Advances in Machine Learning & Artificial Intelligence(AMLAI)

Department of Emergency Medicine, New Life Hospital, Korea

Publications

• Research Article   
  Analog Hawking Radiation in Transformer Neural Networks: Discrete Geometric Horizons, Information Thermodynamics, and Hallucination Suppression
  Author(s): Chur Chin*
  
  Recent advances in deep learning have revealed that large-scale neural networks exhibit emergent behaviors reminiscent of physical systems near criticality. In parallel, analog gravity has demonstrated that phenomena traditionally associated with quantum field theory in curved spacetime-most notably Hawking radiation-can arise in diverse non-gravitational systems. This review synthesizes a comprehensive theoretical, computational, and experimental framework establishing an explicit analogy between Hawking radiation and information flow in Transformer neural networks. By interpreting attention dynamics as a discrete acoustic metric, we show that effective horizons emerge when information flow becomes supersonic, characterized by a Mach number exceeding unity. Gradients of this Mach field define a Hawking-like temperature that naturally induces thermal fluctuations in representation spa.. Read More»
  

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