The article explores the philosophical implications of large language models (LLMs), particularly in relation to human cognition. It discusses the historical context of artificial neural networks and their role as models of intelligence. A significant point raised is the "Redescription Fallacy," which critiques the misunderstanding that LLMs, due to their reliance on statistical operations, are inadequate for modeling cognitive processes. This calls into question the validity of such arguments and highlights the ongoing philosophical discourse about the nature of intelligence and language understanding in artificial systems.
The philosophical discourse surrounding artificial neural networks has largely revolved around their potential to model human cognition, particularly in comparison to classical symbolic systems.
The term 'Redescription Fallacy' describes misguided critiques suggesting LLMs are incapable models of cognition due to their reliance on statistical techniques rather than abstract processes.
Collection
[
|
...
]