Natural Intelligence, Machine Intelligence, General Theory of Information, and all that Jazz: Part I

Video: Ingredients of natural intelligence, machine intelligence, and GTI

Part I: Understanding Natural and Machine Intelligence

The holy grail of computer scientists and information technology professionals is to design and build machines that replicate the capabilities of human intelligence. While trillions of dollars spent have produced impressive results in process automation, intelligent decision-making using insights from machine learning, and a host of very impressive applications with generative AI, the machines still fall short in delivering systems that replicate higher-level reasoning moored to external reality, commonsense, and wisdom. Before we replicate the unique autopoietic and cognitive behaviors of biological systems using machine intelligence, we need to understand the true nature of natural intelligence.

The video above is my attempt to update my knowledge and capture the main ingredients of natural intelligence, machine intelligence as we practice today, and the theoretical foundations of GTI. This Part I devoted to understanding the differences between natural and artificial intelligence using the General Theory of Information. In Part II, I will attempt to capture how, we implement autopoietic and cognitive distributed applications which are cloud agnostic and integrate both symbolic and sub-symbolic computing structures with super-symbolic computing.

Natural Intelligence: Biological systems, while made up of material structures, are unique in their ability to keep the identity of their structures, observe themselves and their interactions with the external world using information processing structures, and make sense of what they are observing fast enough to do something about it while they are still observing it. They inherit the knowledge to build, run, manage their structures, and interact with their environment using neural cognitive capabilities acquired from their genome transmitted by the survivor to the successor. A genome is an organism’s complete set of genetic instructions. Each genome contains all of the information needed in the form of life processes to build the organism and allow it to grow and develop a society of genes. As described by Itai and Lercher in their book (p. 11) “The Society of Genes”, the single fertilized egg cell develops into a full human being without a construction manager or architect. The responsibility for the necessary close coordination is shared among the cells as they come into being. It is as though each brick, wire, and pipe in a building knows the entire structure and consults with the neighboring bricks to decide where to place itself”.

In essence, the source for human intelligence starts from the genome that provides the knowledge to build, operate, and manage a society of cells that work together with a unique identity and an ability to make sense of information received from various senses and take action based on experience. The knowledge is passed on from the successors to the survivors as chromosomes which contain knowledge to create a society of cells that behave like a community, where individual cell roles are well-defined, and their relationships with other cells are defined through shared knowledge and they collaborate by exchanging messages with each other defined by specific relationships and behaviors. DNA provides a symbolic computing structure with the knowledge to use matter and energy to create and maintain stable structures with specific tasks. In addition, the neurons, also known as nerve cells, form the fundamental units of brain and the nervous system which carry information. The brain contains billions of neurons and form complex networks that process information, and update knowledge which is stored in form of associative memory and event-driven interaction history. Both associative memory and event-driven interaction history strengthen connections based on experiences and events. This allows the brain to learn, adapt, and recall information efficiently.

As discussed in the video, current state-of-the-art AI does not consider:

• The sense of “self” – the model of the computer (information processing) and the computed (knowledge representation).
• Associative memory and event-driven transaction history which provide a single point of reference for all reasoning.
• Ability to use experience moored to external reality and using commonsense, ethics, and other knowledge from various sources.

In Part II, we will explore associative memory, event-driven interaction history, meta-cognition, and higher-level reasoning moored to external reality, commonsense, ethics, and other knowledge from several sources in the digital world.