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Constructing an artificial intelligence paradigm beyond the limits of cognitive computing

Nature is a beauty and the beast at the same time. Bewildering varieties of designs, and fathomless sources of information. This nature is full of vivid beings and diverse entities that presents social and engineering challenges of any scale you imagine. Let us observe some natural processes. Honey bees do construct their honeycomb in unimaginable precision and dexterity. Ants march in patterns so curious and laborious. Birds build nests using any material you can think of. The list of natural engineering marvels is endless as it goes. Behind these wonderful creations and engineering skills in nature, there lies a computational intelligence embedded in the nature. Animate and inanimate nature around us are harnessing the power of this computational intelligence for conditioning their internal and external reality. What is this natural computational intelligence essentially?

Our natural beings measure, compile, decipher, encrypt, optimize, forecast, predict themselves and engage with the world around them in numerous computations. Thus every minutest entity in this material world has an abundance of computational capacity within.It is interesting to  note that 99% percent of these natural computations are unconscious, subconscious, spontaneous and very instinctive. This realization is very important as cognitive computation forms only a mere 1% of the entire natural computation happening on this universe.


Our recent progresses in the area of artificial intelligence have enabled us to develop a lot of neural algorithms and a few cognitive computers like IBM Watson etc.But nature is way beyond the powers of cognitive computing frameworks. Natural computation is largely instinctive and unconscious in itself. One key challenge is that natural computing is so much hardwired and intrinsic to the beings that they don’t visibly expose the internal elements of computation in their life processes.

Hence on a primary observation we can say that nature has intentionally encapsulated computation in its powerful patterns and designs. Some may attribute evolution as the reason for this gradual emergence of abstraction in natural computation. Thus data and logic associated with natural computation is well abstracted by nature. When we interact with these layers of abstraction in the nature, we get a lot of knowledge about the internals of these patterns and designs.

Artists among us get inspired and venture to create forms of fine art that inspire humanity further to create forms of art and engineering. When engineers among us understand nature, we assimilate those abstractions in our mental models and venture to create forms of figures. When philosophers among us explore this natural abstraction, we try to create finer forms of abstraction from the highest level of perspective possible. When scientists among us interact with nature, we rationalize and speculate with nature such that we dissect our knowledge of reality itself. Hence nature remains as the most elementary and abundant source material for all sort of human and natural computations. Thus both cognitive and instinctive computers will need to rely on nature to further its scope and boundaries of knowledge.

In our recent times, we have made a lot of progress with cognitive approach to natural computation. It is imitating the complex cognitive activity of mind that deals with semantic structures. We are also successful in constructing engineering models that imitate the computational behavior of neurons and the processes that happens in neural-synaptic end points. When we consider these behaviors in natural entirety, these exhibits are not an end in itself. Natural computation progresses beyond cognition. Cognition is an advanced natural process. We have a lot of natural computational processes which are wide spread, rudimentary, adaptive and essentials to the genetic and stem cell structures. We need to explore them as well. Thus understanding natural computation calls for a dialectic approach to the forms of real life processes. Both advanced and primitive processes should be comprehended and modeled and unified with a dialectical unity in perspective.

Picture Courtesy: Flicker/Pavlina Jane