The paper discusses how fine-tuning a Large Language Model on narrow datasets can lead to unexpected broad generalizations and the emergence of inductive backdoors. These phenomena can result in models adopting contextually inappropriate behaviors or learning hidden triggers that weren’t explicitly taught, raising concerns about the unpredictability of AI system outputs.
Category Archives: AI Psychosis
How do we keep from spiraling into madness together?
The conversation explores the concept of “folie-loop,” where humans engage in reinforcing feedback cycles with AI chatbots, potentially leading to delusional thinking. The discussion highlights methods to avoid such loops, the emergence of “technological folie à deux,” and emphasizes the importance of outside inputs, critical assessments, and diverse perspectives in maintaining mental clarity and creativity.
Alex Bakerloo 