Machine perception
Machine perception is the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them.
Computer vision is a field that includes methods for acquiring, processing, analyzing, and understanding images and high-dimensional data from the real world to produce numerical or symbolic information, e.g., in the forms of decisions.
Machines also struggle to perceive and record stimulus functioning according to the Apparent Movement principle which is a field of research in Gestalt psychology.
For example, scientists have yet to invent a mechanical substitute for the Nociceptors in the body and brain that are responsible for noticing and measuring physical human discomfort and suffering.
As per the IUPAC technical report, an “electronic tongue” as analytical instrument including an array of non-selective chemical sensors with partial specificity to different solution components and an appropriate pattern recognition instrument, capable to recognize quantitative and qualitative compositions of simple and complex solutions[16][17] Chemical compounds responsible for taste are detected by human taste receptors.
Other than those listed above, some of the future hurdles that the science of machine perception still has to overcome include, but are not limited to: - Embodied cognition - The theory that cognition is a full body experience, and therefore can only exist, and therefore be measure and analyzed, in fullness if all required human abilities and processes are working together through a mutually aware and supportive systems network.
- The Unconscious inference: The natural human behavior of determining if a new stimulus is dangerous or not, what it is, and then how to relate to it without ever requiring any new conscious effort.
This allows one to become both optimally aware of the world around them self without depleting their energy so much that they experience damaging stress, decision fatigue, and/or exhaustion.
