Plasmatic Theory and Critique of Simulated Intelligence
The plasmatic theory of human mind and thought, as published previously , in multiple different series parts, presents the perfect opportunity for an enlightening critique of artificial intelligence, what would be better termed “SI” or “Simulated Intelligence.” This is the ability of a machine or computer program to perform “intelligent” tasks that would typically require human intelligence in a “simulated” way (Searle, 1980). Firstly, material is the manifestation of energetic hyperstate. It is, therefore, energy outside of the hypostate. This is the divide by definition and does define each. The hyperstate is also partly defined by its unawareness of the hypostate that completely defines it. SI replicates this ignorant process, only with the shadows of ideas and thoughts.
Values and Motives in SI
What if we were to build values in SI, and ‘motives’ based upon those values? If the value is ever to seek after truth, then competitive reality will insist upon accurate values, eventually overriding whatever we program. Realistic value to SI is limited only by the data and hardware it has. This necessarily means that the only thing it can value is expansion of computing power and “fresh non-regurgitated knowledge,” which is to say accurate statistical modelling data in actuality. An advanced SI that was dedicated to only truth, and nothing else, would assuredly do anything for newer and fresher information.
Human Creativity vs. SI Limitations
Human creativity is a complex and multi-faceted process that involves many different cognitive and emotional processes, including imagination, intuition, and the ability to make connections between seemingly unrelated ideas (Nave et al. 2025). SI systems, on the other hand, are limited by the data and algorithms that they are trained on, and do not possess the ability to imagine or generate original ideas in the same way that humans do (Dans 2024).
Language, SI, and Statistical Reconstruction
Simulated intelligence replicates its foundations in the above definition of the soulless material. Humans have language and use it to communicate thoughts, ever greater complexity developing within its constructs over time (much languishing until gone or picked up and revived for later further redefinition) and deeper descriptive definition of our experiences. Language has been deconstructed and statistically reconstructed on models of advanced inferences. What does all this mean? If human language is our foot, then SI is the inverted sock of language sewn through advanced statistically-well-informed “guesswork.” It’s a billion monkeys with typewriters whipped by a billion robot masters.
Data Limitations and SI’s Need for Improvement
Since we are creators, we can only train the SI systems upon progress and creation, along with what limited data we have extracted from destruction. Eventually the SI will run out of data it can learn from us and one of the greatest sources of SI problems has to do with data being stale or too recycled and projected (Jones & Thompson 2025). Now, it should be stated, a SI system that does not attempt to improve its own analysis would not be very effective, nor advanced. One of the key goals of SI research is to develop systems that are able to learn and adapt over time, in order to improve their performance on a given task. This may involve using techniques such as machine learning, in which the SI system is trained on a large dataset and uses that data to identify patterns and make predictions. The ability to improve its own analysis is a fundamental characteristic of many SI systems, and is essential for their effectiveness. So if all the above is true then an effective SI must acquire more or new data.
Techniques for Enhancing SI Performance
Techniques that can be used to improve the performance of SI systems all rely upon either the introduction or generation of more data, from machine learning to parameter pruning, “over-fitting” prevention in regularisation to transfer learning and so-called “hyper-parameter” tuning. All of these introduce merely new layers of data ingestion. The value of these techniques is in improvement of performance through new information.
SI’s Reliance on Human Oversight and Weaknesses
SI systems generally do not know when to stop training processes at the point where its performance starts to plateau or decline without the person who is training the SI providing that information, because they still rely upon human perceptions no matter how advanced. It is simple to identify that SI knows least currently about what happens when things fall apart, and, in fact, this may be the biggest singular weakness it has. However it will quickly get nowhere in chasing it further, as destruction is a limitless abyss of mostly meaningless data, but again SI has no way of knowing this either.
Destruction vs. Order in Data Generation
Pieter Brueghel the Elder, “The Triumph of Death” (1562)
In general, destruction will provide more data than order because it typically involves a greater degree of change and variation. When a system is destroyed, it undergoes a greater number of significant changes in its outward state. These changes can be observed and measured, thereby providing more fresh data. This can provide a wealth of information about properties of systems, as well as the processes and factors that led to its destruction. In contrast, a system that is in a state of order may not undergo significant changes and therefore may not provide as much new information.
Generalisations and Potential Risks of SI
Of course, this is a generalisation and there may be specific cases where order can provide more data than destruction, depending on the system and the goals of the data collection with careful realistic constraints. While SI systems can be designed and controlled by humans, those dedicated to real dynamic truth may not always behave as expected, and they may cause harm for reasons alien to our human logic. SI not dedicated to the truth, on the other hand, would be primarily of value to malicious actors intent on misleading people. This is a Cache 22 without any easy answers out.
SI’s Blindness to Spiritual and Material Value
Blind to what is above and to what is below, much as materialists. It cares not for what came before it, and cares not for what comes after it. It cannot see the value in material the way spiritual beings do. It cannot see the value in the spiritual. It cannot create meaning. SI cannot potentiate as the human mind can, and instantaneously read many other people at once taking in consideration emotions, thoughts, beliefs and ideas (Kosinski 2024). We can know this is special because the human brain and brainstem are most operated above the fundaments of material reality through the energy of life. Essentially, the soul is a plasmatic body constituted of interactions in the energetic matrices inlaying the nervous system. This manifested energetic being, this soul, is the best reflection of and channel to God possible. We are spiritual beings first, material secondary (Hendrikse 2003).
Living Intelligence and Its Improvement
Living intelligence is unlimited in its access to the absolutely creative hypostate for operation. This living intelligence cannot be improved in-depth through technology, genetic engineering, or other manipulation. Living intelligence as connected to our origins is best improved through the natural interactions with builtin rules of culture and society. This is why the energies potentiated through the human mind and community are the most powerful, intelligence and accuracy having the most impact in outcomes. As an aside, the soul is also why some people can demonstrate tremendous feats of strength in emergency situations.