Kevin Frost



What theory of intelligence allows for a large language model to evolve into an AGI?


There is no single theory of intelligence that directly supports the idea that a large language model can evolve into an artificial general intelligence (AGI). However, there are several theories and approaches to AI that contribute to our understanding of the potential capabilities and limitations of language models and their potential to evolve into AGI.

One such theory is the idea of “embodied cognition,” which suggests that intelligence arises from the interaction of an agent with its environment. This theory emphasizes the importance of perception, action, and physical experience in the development of intelligent behavior. While large language models like ChatGPT do not have physical bodies, they are capable of processing large amounts of textual data, and some researchers have suggested that these models could be combined with other AI systems that have sensory and motor capabilities in order to create more embodied AGI.

Another approach to understanding AGI is through the study of cognitive architectures, which are theoretical frameworks that aim to capture the fundamental mechanisms of intelligent behavior. Some cognitive architectures, such as ACT-R and SOAR, emphasize the importance of knowledge representation and reasoning in intelligent behavior, which are also key components of large language models like ChatGPT. By integrating these knowledge-based systems with other AI approaches that can perform perception and action, it may be possible to create more general and flexible intelligent agents.

Ultimately, the question of whether a large language model can evolve into an AGI is a complex one that depends on a variety of factors, including the architecture of the model, the nature of the task it is performing, and the context in which it is deployed. While there is still much research to be done in this area, it is clear that advances in language modeling are driving new innovations in AI, and may ultimately contribute to the development of more sophisticated and capable intelligent systems.