How GPT Realizes Leibniz’s Dream and Passes the Turing Test without Being Conscious

Large Language Models (LLMs) like GPTs achieve their recent success by building on concepts traced from Leibniz's calculus ratiocinator through Turing's computational models of learning. The article argues that GPTs operate as Kahneman's "System 1"-type processes, lacking mechanisms for consciousness, yet they demonstrate intelligence and the capacity to represent and process knowledge. This capability comes from processing vast corpora of human-created knowledge, which originally required human consciousness to produce but can now be collected, compressed, and processed automatically.

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Abstract

: This article addresses the background and nature of the recent success of Large Language Models (LLMs), tracing the history of their fundamental concepts from Leibniz and his calculus ratiocinator to Turing’s computational models of learning, and ultimately to the current development of GPTs. As Kahneman’s “System 1”-type processes, GPTs lack mechanisms that would render them conscious, but they nonetheless demonstrate a certain level of intelligence and the capacity to represent and process knowledge. This is achieved by processing vast corpora of human-created knowledge, which, for its initial production, required human consciousness, but can now be collected, compressed, and processed automatically.