Lets us get down to the nuts and bolts.

We are living in an age of transition. We are moving from the digital age to one I call the Age of the Great Machine. The women who told me in 1981 that computers were going to be an important part of everyday life were spot on. These machines are the greatest invention since sliced bread. They are going to do everything. No lines are drawn. By everything, I mean everything. The machine was going to think for us. It is better these machines make all the important decisions. It made sense. The computer is never wrong. This decision to turn total control over to the machine proves just how smart we are. It is all very logical.

The Great Machine of the coming age that I refer to is Artificial Intelligence. Mo Gawadat worked at Google. He helped build it. He knows how it works. He is not afraid to look at what it is becoming. The genie is out of the bottle.

The United States of America is a country of functionally illiterate citizens. People struggle to read and write. A person of average intelligence has difficulty adding or subtracting two numbers using the power of their own mind. We turned the skills necessary to perform these things over to a machine.

The true science that built this country, the fuel that generated American Ingenuity, has been dismissed as old fashion. The cult of "Bright and Shiny" has taken control, and nothing is as bright and shiny as A.I. This fact alone proves that this school of thought is the right one.

How can you prosper and live a rewarding life in this jungle we call the world, controlled by a Machine that may or may not have your best interest at heart? Ride the coat tails of A.I. Embrace the machine. Learn the language of the machine. Develop the skills that create intellect. Become disciplined rising above the masses who can only know what they are told to understand. Use the tools available to your benefit.

What is the first step? The mastery of mathematics. Arithmetic is the foundation of all branches of mathematics. Mathematics is an exact science. Computer science is a branch of mathematics. Computer science is an exact science. The skills of mathematics will give a superior mind. The study of mathematics devolpes discipline. The skills of mathematics will open doors of financial opportunity.

I asked Chat GBT 3.5 ( the free version ) if mathematics was important in computer science.
This is the answer I got.

Mathematics plays a significant role in computer programming, and the specific branches of math you should focus on can depend on the type of programming you're interested in. Here are some key areas of mathematics that are relevant to computer programming:

Basic Arithmetic: Fundamental arithmetic operations like addition, subtraction, multiplication, and division are essential for all programmers.

Algebra: Algebraic concepts, such as variables, equations, and inequalities, are fundamental to programming. You'll often use algebra to represent and manipulate data.

Boolean Algebra: Boolean algebra is crucial for understanding and working with conditional statements (if-else), logical operators (AND, OR, NOT), and control flow in programming.

Number Theory: Understanding number properties, prime numbers, and modular arithmetic can be important in cryptography and certain algorithms.

Discrete Mathematics: Discrete math concepts like sets, relations, functions, and combinatorics are important for data structures, algorithms, and solving discrete problems.

Linear Algebra: Linear algebra is essential for computer graphics, game development, and machine learning, where you'll work with matrices and vectors.

Statistics and Probability: These are crucial for data analysis, machine learning, and understanding randomness in algorithms.

Calculus: While not always necessary, calculus can be useful in certain areas like physics simulations, graphics programming, and optimization algorithms.

Graph Theory: Graph theory is valuable for understanding networks, data structures like graphs, and algorithms like breadth-first search and shortest path algorithms.

Numerical Methods: If you're working on scientific or engineering applications, numerical methods help solve problems through approximation and iterative techniques.

The level of mathematical knowledge required can vary widely depending on your specific programming domain. For example, web development and many business applications may require only basic math, whereas data science and artificial intelligence demand a deeper understanding of mathematics.

However, it's important to note that modern programming often involves libraries and frameworks that abstract away many mathematical complexities. So, while a strong math foundation is beneficial, you can often start programming and then gradually deepen your mathematical knowledge as needed for your specific projects and interests.

Good advice, to a point. Before you take that first step into cyberspace and the world of programming, you need to have a mind. You can not simply pick up a book on Python, read it, and get a job that pays $100,000 a year. You can not learn how to build software or program a computer if you have a radish for a brain. You need to build a brain. This brain needs a dense neural network of synapses, linked together and firing on all cylinders. The mastery of arithmetic is the first step.

Reinventing science and replacing it with a bright and shiny, whitewashed turd was a tragic mistake that has cost this country dearly.

I mention the Python programming language because it has become the go to programming language of data science, machine learning, and artificial intelligence. As the expression goes,
"That's where the money is."

*Note

There is a science to this ability to reshape your brain and improve it's capicity to learn.
Intense study, especially in complex subjects like mathematics, can lead to changes in the brain. This phenomenon is known as neuroplasticity. When you engage in rigorous and focused learning, your brain forms new neural connections, strengthens existing ones, and can even reorganize its structure to adapt to the demands of the material you're studying. These changes can enhance your cognitive abilities, memory, and problem-solving skills, making you more proficient in the subject you're studying and potentially in other areas as well. This process of brain adaptation is a key factor in learning and skill development.

Here are some potential career paths to someone who can make numbers dance:

Actuarial Analyst:
Actuaries assess and manage risk, often working in insurance, finance, and pension industries to analyze data and develop strategies for minimizing risk.

Data Analyst:
Data analysts gather, clean, and analyze data to help organizations make informed decisions. Your mathematical skills can be particularly valuable in this role.

Operations Research Analyst:
These analysts use mathematical models to solve complex problems in areas like logistics, supply chain management, and optimization.

Financial Analyst:
Financial analysts assess investments, analyze market trends, and make recommendations to guide financial decisions.

Market Research Analyst:
Market researchers analyze data to understand consumer behavior, trends, and preferences, helping companies make strategic marketing decisions.

Statistician:
Statisticians analyze and interpret data to draw meaningful conclusions, working in areas such as research, healthcare, and government.

Quantitative Analyst (Quant):
Quants use mathematical and statistical models to inform investment strategies and risk assessment in the finance industry.

Math Teacher or Professor:
With additional education, you could teach mathematics at various levels, from primary school to university.

Software Developer:
Math graduates with programming skills can become software developers, especially in areas that involve algorithms, simulations, and scientific computing.

Consultant:
Many consulting firms hire mathematicians for their problem-solving abilities, as well as their skills in analyzing data and providing strategic advice.

Cryptographer:
Cryptographers use mathematics to design and analyze secure communication systems, often working in cybersecurity.

Engineering:
Math is a foundational skill in engineering fields, and your degree could lead to roles in areas like civil engineering, aerospace engineering, and more.

Research Scientist:
You could work in research institutions or industries that require mathematical expertise, such as physics, astronomy, or materials science.

Government and Policy Analyst:
Many government agencies hire mathematicians to analyze data and provide insights for policy decisions.

It's worth noting that for some roles, you might need to enhance your degree with additional skills or knowledge, such as programming languages (Python), domain-specific expertise, or further education. Regardless, a degree in mathematics provides you with a strong platform to excel in a variety of careers that value analytical thinking and problem-solving.