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Artificial Intelligence – A Complete Guide To Programming In C++


We may be in the cusp of a new era with Artificial Intelligence (AI) Technologies. What part can C++ software play in the advancement of artificial intelligence? Read on to find out more.

Is Artificial Intelligence Science Fiction or Science Fact?

We’ve all seen the movies. AI, taking over the Earth and enslaving what it sees as dumb humans. A patient but unyielding HAL 9000 refusing to open the pod bay doors – “I’m afraid I can’t do that Dave” – in Kubric’s masterpiece. The human brain is such a powerful and mysterious part of our body, and we want to know more and more, and dive deeper yet we are still far from copying or exceeding the human brain, long after Alan Turing mathematician, philosopher – and one of the founders of what we have come to call computer science – proposed a test by which a machine could be judged to be truly intelligent. Generally, the best guess is that we may see machines which exhibit enough intelligence to pass the Turing Test in 10 – 20 years, maybe less.

Now we are beginning to close that gap between the real and artificial brain. Advances in hardware are boosting the raw processing technology, combined with ubiquitous high-speed internet and better programming techniques are nudging us towards a new era where machines with artificial intelligence might competently compete with – or even exceed – the abilities of a human intellect.

Nowadays many companies are involved in developing Artificial Intelligence (AI) applications. It is very clear that there is an apparent increment in the issue of patents in the last 10 years. Still, this is also a good research area in academics. Computers thinking like a human are still absent in our world but day by day we are getting much closer.

Artificial Intelligence A Complete Guide To Programming In C++ an image of a bot

A Complete Guide To AI Programming In C++

Introduction to AI

Artificial Intelligence, also called AI refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving. (reference: Investopedia). 

There are many other similar definitions. In addition to the AI term, we should add these terms too. Machine learning (ML) is the study of computer algorithms that improve automatically through experience. While we have all advertisements that say Smart or AI-supported thing, in reality, there is no AI yet. We call all AI-related things as AI Technology. The AI term in its definition may be happening with Artificial General Intelligence also called Strong AI, there is also Artificial Biological Intelligence (ABI) that attempts to emulate ‘natural’ intelligence.

Introduction to Artificial Intelligence in C++
A Simple Artificial Neuron Model in C++
How To Make Artificial Neuron Models in C++

Neuron Models

Do you want to develop your of artificial intelligence application from scratch? Want to learn how you can develop a simple artificial neuron model in C++? In this post we will explain with a very simple artificial neuron example. We have released A Simple Artificial Neuron Model in C++ and Very Simple Artificial Neural Network (ANN) Example in C++ and we also released Array Based Simple Artificial Neuron Model in C++ before. We highly recommend reading Introduction to AI Technologies and them if you are new to AI technology.

Very Simple Artificial Neural Network Example in C++
Structure Based Simple Artificial Neuron Model in C++
Array Based Simple Artificial Neuron Model in C++
Class Based Artificial Neuron Model in C++
Vector-Based Simple Artificial Neuron Model

Artificial Intelligence A Complete Guide To Programming In C++ a phrenology model of a head

Activation Functions

Minimum Artificial Neuron has an activation value (a), an activation function phi() and weighted (w) input net links. So, it has one activation value, one activation function and one or more weights depend on the number of its input nets.

The Activation Function phi() is also called a transfer function, or threshold function that determines the activation value a = phi(sum) from a given value (sum) from the Net Input Function. The Net Input Function; here the sum is a sum of signals in their weights, and the activation function is a new value of this sum with a given function or conditions. In other words, the activation function is a way to transfer the sum of all weighted signals to a new activation value of that signal. There are different types of activation functions, mostly Linear (Identity), bipolar and logistic (sigmoid) functions are known well. The activation function and its types are explained well here.

Identity Activation Function in Neural Networks
Sigmoid Functions In Neural Nets
Binary/Heaviside Step Functions In C++
Gaussian Error Linear Units in C++
Rectified Linear Unit Activation ANN Function
Hyperbolic Tangent Activation ANN Function
SELU Activation Function Works In A C++ App
Sigmoid Linear Unit (SiLU) In A Neural Network C++ App
Gaussian Activation Function In A Neural Network
ELU Artificial Neural Net Functions
Self Regularized Non-Monotonic (Mish) Activation Function

Basic AI Examples in C++

How To Import FANN Library For C++ Builder Windows Projects, This FANN is very friendly and good open library for beginner applications on engineering research and data analyses.
A Simple But Powerful Chat Bot In C++
Brute Force Methods in C++
Minimum Edit Distance Method in Unicode Strings in C++
The SoftMax Function in Neural Networks

REST Examples to Connect AI APIs

What Is The C++ Builder REST Debugger And How Do We Use It?
How To Make A Simple REST Client In C++ And More

Where can I see more articles on AI?

Use this dynamic search on LearnCPlusPlus.org

Two Main MIT Videos about DL, ML & AI Introduction

Note that this is publicly available third-party content over which Embarcadero has no control or association with the authors. We link it here for educational purposes.

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About author

Dr. Yilmaz Yoru has 35+ years of coding with more than 30+ programming languages, mostly C++ on Windows, Android, Mac-OS, iOS, Linux, and some other operating systems. He graduated and received his MSc and PhD degrees from the Department of Mechanical Engineering of Eskisehir Osmangazi University. He is the founder and CEO of ESENJA LLC Company. His interests are Programming, Thermodynamics, Fluid Mechanics, Artificial Intelligence, 2D & 3D Designs, and high-end innovations.

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