The new Python profiler increases the power of Python very much.

 The new Python profiler increases the power of Python very much. 

The Python language is an effective but slow programming tool. Python is a very popular tool in network programming. But because it's slow it is problematic in complicated solutions that run on network-based decentralized platforms. Things like AI-based Bing and Chat GPT are making programming very easy, and they can create very complicated solutions in any public and open programming language. However, those programming tools do not remove the limits of the programming language itself. 

In complex and complicated solutions the program is divided into cells. Each of those cells involves different types of information. And each of those cells is responsible for certain reactions. Another reason for cell-based programming is simple. If one of those cells is corrupt that minimizes damage. 

The problem with AI is how it can select the right cell. If AI selects a cell from an interface that controls the physical machines that thing can cause catastrophe if the selected cell is wrong. That means there must be something. That simulates the reaction before the AI makes anything. This means the AI should have layers written with different programming languages. That it can pre-process information before reactions. 

"Researchers from the University of Massachusetts Amherst introduced Scalene, a cutting-edge Python profiler. Unlike traditional profilers, Scalene uses AI to both identify and suggest fixes for code inefficiencies. This development gains significance as the future leans towards better programming for speed improvements". (ScitechDaily.com/Turbocharged Python: AI Accelerates Computing Speed by Thousands of Times)

All of those cells handle one type of situation. And if the system must react fast, that means it needs multi-level programming architecture. The AI-based applications involve extremely complicated and large code structures with even millions or billions of databases and database connections. 

If the AI must go through all that code it takes too long. But if the AI has some kind of profiler that profiles the situations that the AI sees. That helps it to select the right cells from its structure. The faster structure below the Python level makes it possible to pre-select cells. The difference between AI solutions and regular computer programs is that AI is a non-linear tool. It requires the possibility to jump back and forth in the code. 

The faster C++ core under Python makes profiles about situations. That sensor gives it. Then that C++ layer selects the right Python cell. The C++ layer simulates the sensorimotor cortex. And Python layer is like the cerebral cortex. 

So there is a possibility that Python requires some other interface that runs below Python code. That other interface might written by using some other programming language like C++. That is faster than Python. The idea is that the inner code analyzes reactions that the Python interface makes in certain situations. The C++ interface under Python can jump into Python code and pre-select the program modules suitable for a certain situation. 

That kind of faster structure below the Python interface makes the structure look like a brain. The Python structure is like a cerebral cortex, and the C++ layer is like sub-consciousness. The faster C++ can also act as a reflex layer that reacts to fast situations. The Python layer can give observations into that C++ layer, that profiles the situation. And then that faster layer will select the right cell from the Python layer.