In a recent opinion piece, John Thornhill highlights a growing enthusiasm for generative Artificial Intelligence (AI) while also critiquing its limitations. Thornhill correctly points out that the use of Human language is not a probabilistic Bayesian process, contrary to what some may believe. Linguistics luminaries such as Noam Chomsky and Andrea Moro have shown that language acquisition involves learning a set of grammar and linguistic rules, which are housed in a specific part of the brain.

Thornhill also raises important questions about what these AI systems reveal about human speech and its connection to reality. While these models may generate errors due to the garbage in, garbage out phenomenon, a more profound consideration is the impact on human cognition. Jiddu Krishnamurti, an Indian mystic, pondered the consequences of machines thinking for us.

However, Thornhill acknowledges that current AI systems do not come close to passing the Turing Test, which is the benchmark for human-like machine intelligence. Buddhism, centuries ago, recognized that human thought could be classified into different natures, with speech being one aspect. Unfortunately, many humans are influenced by negative mental narratives driven by ego-based greed, hatred, anger, and narrow-minded biases.

In conclusion, generative AI offers great potential but also poses limitations. It is crucial to understand the relationship between AI-generated speech and human cognition. Thornhill’s critique prompts us to consider the implications of relying on machines for our thinking processes and encourages a deeper exploration of the nature of human thought.

Sources:
– Noam Chomsky
– Andrea Moro
– Jiddu Krishnamurti

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