Artificial Intelligence AI can be simply defined as solving problems through automated algorithms.

In this article, we explain the basic prerequisite skills of a future AI programmer and how he can improve his abilities in the field of artificial intelligence programming.

Finally, we use AI to test the correctness of the well-known theories of relativity and quantum mechanics introduced by the giants A. Einstein and E. Schrödinger more than a century ago.

The numerical results are stunning because they show that the well-established theories of relativity and quantum mechanics are only partially true and contain inherent flaws.

It is worth mentioning that many of our respectable contributors and readers frequently ask how do you judge and correct the scientific work of the giants A. Einstein and E. Schrödinger?

Does this mean you are smarter than both of them?

The answer is that we use AI.

It is the artificial intelligence of the Cairo techniques and its B-matrix algorithms that is smarter than A. Einstein and E. Schrödinger and not the author himself.

An AI programmer needs to have good programming skills, primarily in Python, and a grasp of algorithms, data structures, and mathematical concepts such as linear algebra, calculus, and probability. He/she needs to be proficient in machine learning libraries such as TensorFlow or PyTorch and be knowledgeable in neural networks, natural language processing, and computer vision. Problem-solving skill, data manipulation ability, and familiarity with cloud computing and big data technologies are also required. Additionally, AI programmers must keep themselves updated with the latest in AI and have a sound analytical mind to be able to develop and tune intelligent systems.

Ismail Abbas M. Abbas

For a given problem, there are too many different solutions and too many different approaches or workflow diagrams.

i-The old way where the solution is the result of processing the input data through the intelligence of the human brain (shown in Figure 1) is expensive and time-consuming.

ii-The new way of artificial intelligence AI (shown in Figure 2) is more powerful, cheaper and less time-consuming.

Note that artificial intelligence (AI) is simply defined as solving problems through automated algorithms. The practical application of AI dates back to the time when the first primary computers were powered by punch cards and vacuum tubes. At that time, humans were thinking and wondering what these computers could do when they are even more advanced, with larger memories and faster processors! What would this mean for humanity?

Could they help us solve our biggest challenges, from climate change to global food and water shortages? In this answer, we present and explain:

1- the basic prerequisite skills of a future AI programmer.

2- How a beginner AI programmer can improve his abilities in the field of artificial intelligence with more knowledge about statistical transition chains such as Markov and B-matrix chains.

3- Finally, we use AI to test the correctness of the well-known theories of relativity and quantum mechanics introduced by the giants A. Einstein and E. Schrödinger more than a century ago.

The difference between the old way of thinking for decision-making via a human meeting dealing with paper documents and the artificial intelligence method of computer processing of electronic input and output data is illustrated in Figures 1 and 2

To be continued.First of all, the human who chooses to work in AI to find solutions to the world's great problems must be exceptional or one of the best [1].By one of the best, we mean, in addition to high intelligence, high activity, that he must have excellent knowledge.We recommend the following knowledge:1- Fortran or C++ programming language(Not PYTHON or MATLAP)2- Linear algebra, complex analysis and probability and statistics.3- Statistical transition matrix chains such as Markov chains and/or B matrix chains of Cairo techniques.4- Basic universal laws in physics.3- Statistical Transition ChainsToday, we know only two statistical transition chains, namely the well-known Markov chains and B-matrix chains.They require a better physical and mathematical knowledge of some basic terms,1- Theorems on closed volume and closed surface.2- Dirichlet boundary conditions.3-Source/sink term.4-Theorems on closed control volume such as,Conservation of total energy and entanglement of energy density.5-Transition probability and resulting statistics.We believe that statistical transition chains are one of the best tools to generate efficient programming of artificial intelligence.-How does AI work?

Desde mi punto de vista, las habilidades Técnicas Fundamentales serían:

1. Programación: Dominio de lenguajes como Java, C++, R o Python.

2. Matemáticas y Estadística: Conocimientos sólidos en cálculo, álgebra lineal y teoría de probabilidades.

3. Algoritmos de Machine Learning: A. de regresión lineal, árboles de decisión, y redes neuronales.

4. Manejo de Datos: Manipulación y análisis de datos con herramientas como Pandas, NumPy y SQL.

5. Frameworks y Bibliotecas de IA: Familiaridad con: PyTorch, Keras, TensorFlow.

Soft Skills Elementales

1. Comunicación Efectiva.

2. Pensamiento Crítico y Resolución de Problemas.

3. Trabajo en Equipo.

A striking example of Einstein's defeat by artificial intelligence is chess.

Einstein played chess regularly (because he believed it could improve human intelligence), especially with his close friend E. Lasker.

E. Lasker was a professor of mathematics and world chess champion at the time.

The debate between the two giants went as follows [1]:

Einstein: I suppose chess is a fake game because the white player has the first move and should therefore have a forced win!?

E. Lasker: But no. The first move advantage for the white player is counterbalanced by the advantage of greater information for the black player.

Therefore, white's advantage decreases as the number of moves increases.

Normally, before the 20th move, both sides are exactly equal for any arbitrary opening.

Einstein worked hard on this problem but to no avail.

He eventually announced that the complexities of chess had defeated the human brain.

It was only at the beginning of the 21st century that the world got a precise answer to this problem.

Artificial intelligence scientists introduced two supercomputers A and B equipped with cutting-edge AI algorithms.

When supercomputers A and B played chess against each other, all games ended in a draw for any type of opening!

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Did Einstein regularly play chess?, Quora Q/A.