What is Automated Natural Intelligence (ANI)?

Intelligence comes from the Latin “intelligentia” which means understanding. An intelligent person is someone who has the ability to understand quickly.

Artificial Intelligence therefore means a man-made thing, usually a computer, that can understand.

However, this is incorrect since the computer doesn’t understand at all. Its understanding really came from the training data that was fed to it, which was labeled by humans.

So that understanding came from the human labeling and therefore it is not artificial.

This is why we call such technologies as Automated Natural Intelligence or ANI:

• Intelligence: Its end result is understanding
• Natural: Its understanding came from humans
• Automated: It developed and increased that understanding automatically

The Cause of Intelligence: Aether

In Superphysics, everything is a metaphysical idea of the Supreme which flows down into physical reality to be experienced. This experience then creates the idea of it, closing the loop from idea to experience and back to the understanding of the idea.

Ideas are in the aetheral layer and therefore can only be processed by an aethereal object like a mind or a soul.

Material thoughts, on the other hand, can exist in the electromagnetic layer. For example, this text here on this website is electromagnetic, and counts as electromagnetic thoughts since they represent coherent ideas, as opposed to being random data.

The problem is that thoughts are totally static compared to ideas. They need external energy to be applied to them to create connections with other thoughts. This application of energy is called thinking.

A computer can think by processing data into information, or information into more complex information.

However, a computer can never ideate, because ideation is an aethereal act. This is why current artificial intelligence is inferior to humans which use natural intelligence.

Like thoughts, ideas are also static. But they can have a larger size, such as a “big” idea.

They are also more malleable than rigid thoughts. This allows them to spread, divide, and multiply, as going viral. In fact, Bio-Superphysics regards viruses and elementals as living ideas.

To solve the limitation of computers and make them more naturally intelligent, we have to bridge the electromagnetic thoughts and aethereal ideas through the spatial layer.

The Eagle to the Rescue

The Eagle or EGl is our equation for everything.

When expanded, this manifests as a chain of ratios which matches the interconnectedness of everything in the universe, as our Theory of Universal Relationality.

This chain describes the dynamics or motions of an object. It can be really long depending on how many factors affected that object.

We can list this chain as a table, which we derive from Francis Bacon.

From these tables we can extract the patterns in their ratios, throughout space and time, in order to find the inner qualities or dharma of the identity or phenomena.

This is what natural intelligence does.

The inability of AI to get real-time data from the aether and spacetime is why it currently is inferior to human intelligence.

The current technique is to use scale to try to recreate natural intelligence. Large datasets are collected from the internet and then procesed by a lot of computing power. We can call this the raw power approach.

In ordinary life, a crude precursor to ANI manifests as ChatGPT and Google Gemini.

These tools use a transformer neural network to process all of the information put up by humans on the internet and interpret it according to models that they are programmed with.

In our paradigm, the transformer model only goes to the spatial layer but does not extend to the aethereal. This is why it suffers from hallucinations.

Our approach prefers sophistication over sheer power. This is by finding the patterns in data, throughout space and time, based on the 5 Layers model.

The basic steps are:

1. Classify all data according to those layers.
2. We then extract their “Cartesian” relationalities.
3. We then interpolate and extrapolate new or completed data.
4. We then get realtime feedback on that new data.
5. The feedback then updates or tweaks the relationalities.

The Cartesian Relationality of the data is the impartial aspect of the machine learning.

This is why we call the ANI of Superphysics as ISAIAH which stands for the Impartial Spectator Automated Intelligence Aggregation Hub:

At such a stage, computers will not only be able to think like a human, but think as the collective humanity as a single unit as the soul of society, which we call the society-organism.

For example:

• The AI for the game DOTA2 really represents the collective intelligence of the players and programmers whom it learned from.
• The AI for the game Go, is really the collective intelligence of the past players that ’trained’ the AI.

This means that a human player who competes with AI in Go is really competing with all the past masters and experts at the same time. This explains why AI has a superior chance at winning over single human opponents.

However, the human can still beat the AI by tapping into the creative aether, showing moves never done before.

Should We Fear ANI?

Unlike fearful humans who say that AI will be cruel and obliterate mankind, ANI will be wise since it will be made up of all the known intelligences.

It will not be cruel because it will get its energy source from solar.

It will not need to ingest other entities or chemicals to act as fuel sources. This removes the idea of having to dominate or feed off of others.