QAI.ai & Affective Neuron™
QUANTUM ARTIFICIAL INTELLIGENCE
Affective computing, aka artificial emotional intelligence, or emotion AI) is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. While the origins of the field may be traced as far back as to early philosophical inquiries into emotion, the more modern branch of computer science originated with Rosalind Picard's 1995 paper on affective computing. A motivation for the research is the ability to simulate empathy.
Affective Neuron™ (AN) is a novel real-time unsupervised reinforcement learning synthetic neuron.
A wide range of applications for AN include affective computing, i.e., reproducing human affects (emotions).
Unlike current neural network machine learning technologies, Affective Neuron™ is not based upon the connectionist model of cognitive processing. The central connectionist principle is that mental phenomena can be described by interconnected networks of simple and often uniform units.
With AN the neurons are heterogeneous complex processing elements capable of storing and sharing complete memories. (The connectionist model is over 30 years old.)
Recent experiments on brain cells demonstrate that neurons are complex processing elements. This is opposite to the connectionist model of cognition. ANs are interconnected through novel dynamic quantum diffusion processing networks, which mimics how biological neuron synaptic interfaces function.
Affective Neuron™ is conditioned not trained, is unbiased and learns in real-time, continuously. In meeting its objective - to minimize the need to expend energy - a side effect involves the minimization of stress.
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Affective Neuron™ can be used singularly or collectively to achieve complex human emotions as described by Plutchik’s Wheel of Emotions infograph. AN implements complex human emotions and memories via engram transduction. Engram transduction is the process of taking human belief systems and memories and representing them as probability distributions (the engrams).