Abstract:The critique of Chomsky by Geoffrey Hinton, often referred to as the “Godfather of Artificial Intelligence”, raises profound questions about the intersection of linguistics and artificial intelligence. This paper explores four critical dimensions where large language models are fundamentally challenging traditional linguistic paradigms: (1) Should we pursue macro or micro linguistics? This debate fundamentally concerns the expansion of linguistic research objects and methodological transformations. The current academic landscape urgently requires a conceptual shift from a narrow, discipline-confined linguistic perspective to a comprehensive, interdisciplinary approach. The proposed “macro linguistics” advocates that macrolinguistics can integrate with disciplines such as humanities, science, medicine, and engineering, and span various domains like phonetics, grammar, semantics, and pragmatics, offering vast potential. (2) Are language and thought inseparable or distinct? The question challenges traditional dichotomies, and the current research argues that Human thought cannot be entirely separated from language. Communication is the primary purpose of thought and thought loses vitality without novel information. Artificial attempts to disconnect thought from communication are counterproductive. (3) Is language acquisition innate or experiential? Artificial intelligence has significantly challenged Chomsky’s innateness hypothesis by abandoning the theory of language as a pre-programmed, innate capacity and embracing language as fundamentally experiential, achieving milestone successes through experience-based learning models. (4) Can AI possess thought or even life? The paper presents a nuanced perspective on AI’s cognitive capabilities. We argue that artificial intelligence cannot possess life in the biological sense. AI’s language is fundamentally disconnected from genuine thought, linguistic fluency does not equate to autonomous thinking and AI remains dependent on human intelligence and control. Without human intelligence to guide and control, AI will accomplish nothing. The conclusion emphasizes human agency: we must learn to navigate and harness artificial intelligence, adapting to this new technological landscape to create a more promising future.