AI language models, like the ones discussed by Jeffrey Hinton, are essentially fitting a model to data with millions of features and billions of interactions. They are trying to comprehend strings of discrete symbols and feature interactions on a large scale, representing the best model we have of human understanding. While some believe this indicates a step towards sentience, others argue that understanding does not equate to sentience. The concept aligns with the idea of finding signals from noise, with the functionality potentially being replicated in non-biological substrates. This adaptively learning model is reminiscent of genetic algorithms, showcasing unexpected efficiency in grasping complex tasks quickly.

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