Consider the hypothetical case where an abundance of computing resources is available to an AI system. In this case, there will be no need to achieve strict optimization goals through undergoing a time taking learning process to compensate for a lack of resources. The machine will follow simple instructions instead of complex machine learning algorithms eliminating speculations about machine’s ability to reason.

Consequently, as technology advances leading to an availability of computing resources, knowledge, in the form of data, would be critical to the performance of an AI system as represented by the correctness, unbiasedness, and informativeness of its responses. On the other hand, machine's reasoning capabilities such as its ability to generate fluent, coherent and user engaging responses would become secondary.

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