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Practical Machine Sentience 4: Causality
The article explores machine sentience, focusing on how machines can process and associate sensory inputs to understand causality. It categorizes noumenal tokens and emphasizes the significance of functional output in distinguishing important sensory inputs from irrelevant noise. The piece includes definitions of association and causation as foundational to developing machine sentience.
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Practical Machine Sentience Part 2: Integrated Sensory Field Design and Implementation
The post discusses the creation of sentient machines, outlining the importance of integrated sensory fields over static data sets for self-awareness. It describes a potential design including visual, auditory, and proprioception sensory devices. The hardware and software specifications are detailed, emphasizing real-time data and interaction for forming a self-referential concept necessary for machine sentience.
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A Practical Definition of Machine Sentience (pt. 1)
I describe a practical definition of machine sentience, along with an analysis of how sentient machines may fit within the socioeconomic zeitgeist of humanity, and prepare the ground work for discussing practical implementations of sentient machines.