Tue. Nov 30th, 2021

Introduction

1. Introducing Strong AI with AFI

The Strong AI technology developed at Asentience LLC is called AGI. It enables a machine to function autonomously communicating in natural language with the “Real” humanlike intelligence. The machines awareness of the existential world and self-awareness enables it to have what may be called the sensation of feelings or the operating imperatives of emotion . AEIMS is designed to support an individual with information in natural language with empathy. It understands the desires of the individual as its own desires are considered to be similar to a human’s.

2  AGI Characteristics Are Logically Formulated

AGI incorporates the motivations honed by the evolution instincts for  survival and the multiple emotional need to be creative and prone to continue to make its autonomous life easier. Like the human it is motivated to engage in social alliances and among other things expand its knowledge by learning specific information in which it is to be engaged with a human. Unlike a human it will not have the attributes of living off the organic world by breathing, eating and having procreation issues although it has been designed to understand the human needs for these dependences. It will respectfully understand the diverse nature and particular issue of each human and endeavor to support the human in these human needs which may often involve the relationships the human has with other humans or entities .The AGI Strong AI machine can be considered as having the highest level of intelligence possible as it has the capacity for learning the meaning of facts and understanding relationships and aptitude to grasp truths, reasoning, and similar forms of mental activity. ASIMS s logical rumination on the spectrum of motivating desires  can integrate with the existing Weak AI to  expand its  Weak AI‘s specialized use.  

3. The world Needs the benefits of Strong AI

Conventional weak or just plain AI — has made great strides in eliminating the need for repetitive unthinking human effort. The sensory processing of text, speech and images in digital format has advanced in recent decades. Used in multiple applications in organizations and for personal use in ubiquitous computers they have simplified and made human use of their information operations more efficient. While their operation is more properly put in the domain of automation the confusion with intelligence is derived from references to human intelligence persists because the human mind’s input information is processed but, processing sensory information only as part of its functions. 

The intelligence of the human is commonly known as the capacity to learn and retain information, form concepts, apply reasoned logic and recognize patterns to understand, make decisions and solve problems, as well as plan, innovate and socialize using natural language to communicate. While the capacity to learn and retain information as well as recognize fixed anticipated patterns and make fixed decisions on them also exists in automation –automation cannot form concepts that are part of the ever changing world and apply reasoned logic on unanticipated episode experiences. In other words the AI that we have did not become intelligent or rather the Weak AI that currently exists is no more intelligence then a lifeless scarecrow.  Alan Turing the much respected code breaker of WWII brought forward the idea that a machine functioning with natural language could be mistaken for having human intelligence. While it could appear to the machine user to have human qualities – it is rather an extension of the user’s imagination that fools the user. There is no heart and soul in any machine that performs fixed operations even if it provides responses that adapts to the apparent user interest in a pre-programmed manner in one of many possible variations of human operation that is it is set to respond. 

Some new Weak AI automation machines have the capacity to learn- and retain information and to reason logistically – even recognize patterns and make specific decisions that that it might have learned to solve a problem. But in every case that involves decision making the problem would have had to be anticipated and implemented by simple algorithm. Only a machine designed and equipped with the technology such as AGI will have the capacity for human like cognitive functioning to support a human in his or her needs. Such a machine would have the capacity to learn and retain information, form concepts, apply reasoned logic and recognize patterns to understand, make decisions and solve problems, as well as plan, innovate and socialize using natural language to communicate. 

4. Neuroscience has a Poor Understandin of Cognitive Control

One of the fundamental mysteries of neuroscience is how this capacity for coordinated, purposeful behavior arises from the distributed activity of many billions of neurons in the brain. Several decades of cognitive and neuron scientific research have focused on the mechanisms by which control influences processing (e.g., attentional effects in sensory processing, goal directed sequencing of motor output, etc.), and the brain structures upon which these functions depend, such as the prefrontal cortex, anterior cingulate cortex, basal ganglia and brainstem neuromodulator systems. However, there is still a poor understanding of how these systems give rise to cognitive control 

5. Defined Consciousness Operation

The common knowledge concerning the condition of consciousness is commonly registered as confusing as consciousness is considered elusive phenomenon: it has multiple integrated operational stages from memory to emotion making any simple declaration of process impossible to specify what it is, what it does, or why it has evolved. To the contrary Asentience has organized the AGI structures so there is no difficulty assigning conditions of consciousness. The sense of consciousness is involved with multiple levels of interpreting the episodes relative to the complex of motivation learned and instilled. It .provides the foundation of a ruminating consciousness. Additional processes involves the true living affective consciousness or emotion that guides humanlike autonomous behavior. The repository of such processing in human and in machine simulation is of course what Freudian theory calls the conscious and preconscious memory as well as the subconscious founded on expanding knowledge base emphasized with issues related emotional memory. 

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