The Recognition Artificial Memory (RAM) Theory
Artificial Memory Recognition Technique
Abstract
Humans who know each other well need only exchange a few words to achieve mutual understanding, whereas machines must transmit every bit in its entirety. This book introduces the Recognition Artificial Memory (RAM) theory. This theory models how artificial systems recognize meaning from shared memory, rather than relying solely on the signals being transmitted. The RAM theory is structured in two layers: A mechanistic layer: five models inspired by the thalamus, amygdala, hippocampus, prefrontal cortex, and an authenticity verification function. Together, these generate a "RAM Scorecard." An information-theoretic layer: four theorems that quantify the meaning retrieved from memory, measured in "RA" units. These theorems address the limits of the meaning-retrieval rate, semantic capacity, the impact of memory mismatches, and guarantees of authenticity. In the case of a 10 dB AWGN (Additive White Gaussian Noise) channel, shared memory increases the meaning-retrieval rate from 2.77 to 3.64 bits per channel use—equivalent to a 3.8 dB power saving. Applications are discussed across six sectors: telecommunications; banking; healthcare; manufacturing; education; disaster management. The book also explores the development of artificial intelligence, including RAM-AI architecture, retrieval-augmented generation, and semantic communication. The final three chapters offer philosophical and spiritual reflections on human memory and the memory of the spirit, the role of artificial memory in life, and the digital recording of one’s life. The boundaries between the realms of science and faith are clearly delineated. Keywords: RAM theory, artificial memory, semantic communication, information theory, RA unit, artificial intelligence.
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