Perception

Human intelligence comes from an amazing duality of arriving at conclusions based on perception of patterns, and the contrary, conclusions based on very structured and rational decisions. Both forms are distinct, but complementary. Machine-based intelligence also comes in two forms: Deep learning based Artificial Intelligence interprets patterns in data to arrive at conclusions and hence, mimics the perception-based intelligence of our brain whereas; and standard instruction-by-instruction computing mimics the rational intelligence of our brain.

We have always wondered why we can easily recall a song’s tune, but not the words. we can remember a face better than the name. we can detect the smell of a specific perfume, but not label it. we can blindly feel a fabric and tell if it is silk, wool, or cotton, but we cannot exactly say why.

It seems as if we can store and recall complex patterns of sound, face, smell, taste, and feeling better than a rational or verbal description. Perception is our ability to see, hear, or become aware of something through the senses. Perception is derived as a single unified awareness from sensory processes. However, when we do logical thinking involving physics, mathematics, planning, calculations, accounts or formulating strategy and tactics, there are very few patterns from the past. Does our brain deal with patterns differently than with logical situations?

Most AI systems today are based on Deep Learning, where learning happens through exposing the AI system to tens of thousands of illustrative examples. Deep Learning method involves absorbing intricate details and subtle nuances in pictures, videos, or sounds into the parameters of the neural network of the AI system. After the training, the AI system is able to perceive the input data based on patterns in images, faces, objects, movements or sounds fed into the system. The AI system decision-making is based on the perception of the input data patterns, behaving like the right side of the brain — specializing in perceiving patterns.

AI deals with understanding patterns in the input data for a situation and deriving perceptions based on its deep learning about a specific topic. These perceptions are expressed as a “level of confidence” for the decisions to be taken for that situation. AI is, in effect, Artificial Perception. An AI machine mimics the perceptional ability of the human brain.

Today’s AI systems, even with its narrow and limited scope, is still capable of revolutionary changes to how we live and work. It offers incredible opportunities for simplifying and personalizing the use of products and offering radically new services. We are just at the very beginning of a massive change.

In summary, we can say that just like two major decision-making skills of our human brain — via perception of patterns and rational, via logic — are also reflected in computing-based decision making. Today’s AI, based on Deep Learning techniques, lead to perception-based decisions whereas, standard computing, like in a personal computer, is based on structured logic for rational decision making. Better and balanced decisions come from combining the best of both flavors.