The new approach for true machine cognition is a dynamic and generative geometric system with mathematical precision.
It doesn’t guess; it just works. Every time.

Whatever you do, you invariably realize that you are something that just works. Every time. That is one of the things that gives you the perception of “uniqueness” or “specialty” (along with the fact that you cannot be defined by what you work “on”). Its that you always work. Always and whenever.

But that perception is something a posteriori relative to that “thing” that works. Get the point? You can only get it… because you work.

An example of why I have a saying that, not being meant to be interpreted literally, is:

There is no school worthy of that name besides the School of the Holy Ghost.
There is no academy worthy of that name besides the Military Academy.

All the rest is superfluous and just a scheme designed to bog people down.

Differences between my approach to AI and the traditional symbolic approach:

• My approach produces reasonings with an arbitrary number of assumptions and end goals
• Lisp and Prolog have to be coded by you to work as you intend, but my approach organizes the information and the rules by itself
• Lisp and Prolog use a linear navigation in the solution space (“backtracking”) while my approach is non linear
• My approach is a geometric system

In fact, my approach is so non linear that it works in multithreading already natively. That is, the reasoning is constructed in parallel at the same time and consolidated in real time.

That is why it is scalable to much complex problems, unlike Prolog or Lisp, and that is something you need to get to human level intelligence and beyond.

As for the comparison between my approach and statistical approaches such as LLMs, the engineers’ favourite toy, well… I started using geometry for AI when everybody else was masturbating with LLMs. Today every new paper claims to improve LLMs with geometric approaches.

Draw your conclusions.

When discussing the way the pyramids were built we cannot afford to ignore one variable: TIME. Because what seems to be the hardest task becomes feasible with simple approaches in a sufficiently long timeframe.

The great pyramid (GP) took about 26 years to build with its 2.3 million blocks. We could consider the average time per block (4.12 days) to expect that at most it took about 8 days to place the hardest blocks. But that only has meaning under the assumption that the timeframe does not depend on the location of the block inside the GP.

A much more meaningful result is to average per course (block layer, or step, which total 206) because the added difficulty of moving bocks higher is somewhat cancelled by the fact that higher layers take fewer blocks to complete. This gives about EIGHT YEARS per layer as average, hence at most it could have taken SIXTEEN YEARS to complete a layer. 16 years is more than enough to move a 9 ton block up to the summit of the GP — with very simple mechanics.

Now you can divide the height of the pyramid by the timeframe to completion and you get the most simple formulation of the Egyptian pyramid building technique:

They only had to solve the mechanical problem of moving a several ton block up by X cm each time, making sure it cannot slip back down, and probably only do it once per day