The Basics of Artificial Intelligence

The Basics of Artificial Intelligence: History, Types, Branches, and More!

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What’s the current hot buzzword in the tech world? Without a thought, it has to be Artificial intelligence (AI), and for good reason. If you’ve ever used Apple’s Face ID, ChatGPT, or Alexa, you’re most likely familiar with AI. Since it’s already a part of our everyday lives, it’s vital that we understand the basics of it.

Whether you’re a business owner thinking of integrating AI into your business or someone trying to make the most benefit of it, you’re at the right place. This blog will discuss the various types of AI, branches, history, and programming languages used for integration.

Keep reading as we delve into the fascinating world of AI and unravel its vast potential and impact.

What Is Artificial Intelligence?

Artificial intelligence (AI) is revolutionizing how we live and work, but what exactly is it? In its simplest form, AI refers to the simulation of human intelligence in machines such as computers, computer-controlled robots, or software programmed to think and learn like humans.

The Complete History of Artificial Intelligence

The history of AI dates several decades back to the early 1900s. And to this day, it is continuously evolving. Here are some notable achievements:

1950: Alan Turing introduces the concept of a “universal machine” capable of mimicking any other machine’s behavior, laying the theoretical foundation for AI.

1956: John McCarthy organizes the Dartmouth Conference, marking the birth of AI as a field of study.

1969: The Shakey robot, developed at Stanford Research Institute, demonstrates basic problem-solving and navigation abilities.

1997: IBM’s Deep Blue defeats chess world champion Garry Kasparov, demonstrating the potential of AI in complex strategic games.

2012: The emergence of deep learning, facilitated by large-scale neural networks and improved computational power, leads to breakthroughs in computer vision, speech recognition, and robotic process automation (RPA).

2018: OpenAI releases GPT-2, a language model capable of generating coherent and contextually relevant text.

2020: AI plays a critical role in assisting with the global response to the COVID-19 pandemic, aiding in data analysis, drug discovery, and vaccine development.

2023: Ongoing advancements in AI continue to shape various industries, including healthcare, finance, transportation, and more.

These are just some of the countless milestones in the history of AI. It is a field constantly developing, and it is not possible to foresee what the future holds. Nevertheless, one thing is for sure: AI is here to stay, and it is likely to have a profound influence on our lives in the years to come.

Types of AI Based on Capability

Capability-based artificial intelligence types categorize AI systems based on their abilities and level of autonomy. It has the following three types:

Artificial Narrow Intelligence (ANI)

Also known as Weak AI, Narrow AI refers to AI systems designed for specific tasks or domains. These systems excel in performing a specific function or solving a particular problem but lack general intelligence. They use machine learning and neural networks to perform specific tasks. Examples include voice assistants like Siri and Alexa, image recognition software, and recommendation algorithms used by streaming platforms.

Artificial General Intelligence (AGI)

General AI, also called Strong AI, refers to AI systems that possess human-level intelligence across a wide range of tasks and domains. These systems can understand, learn, and apply knowledge like humans. However, achieving true General AI is still a theoretical goal with work in progress. The groundwork of AI could be built from generative AI tools like ChatGPT.

Artificial Superintelligence (ASI)

Superintelligent AI surpasses human intelligence in virtually all aspects and capabilities. It represents AI systems that possess cognitive abilities far beyond what humans can achieve. Superintelligent AI is hypothetical and often associated with concerns about its potential impact on society and humanity. Achieving Superintelligent AI remains an open question and active research and speculation area.

Types of AI Based on Functionality

Functionality-based types of AI are categorized based on their areas of expertise and specific capabilities. They focus on the practical applications and functions that AI systems can perform.

Reactive Machines

These AI systems are focused on the present, reacting to inputs in real time without any memory or ability to learn from past experiences.

Limited Memory

AI systems with limited memory can retain and utilize a certain amount of past data, enabling them to make more informed decisions based on historical information.

Theory of Mind

AI systems with the theory of mind possess the capability to understand and attribute mental states to themselves and others, allowing for a deeper level of social interaction and interpretation.


Self-aware AI systems have consciousness of their existence and identity, which includes recognizing their thoughts, emotions, and actions, although this concept is still largely theoretical and under development.

Top 4 Languages for AI Integration

To integrate artificial intelligence into your business, some AI programming languages should be there in every developer’s toolkit. There isn’t any one best programming language for AI, but a handful of suitable ones that can make your AI integration dreams come true.


Python was created way before AI became mainstream. It is the most used AI language for machine learning and is popular due to its creation as a powerful data analytics tool. Python is ranked top because it was developed with AI-specific frameworks such as TensorFlow, Keras, PyTorch, sci-kit Learn, etc.


Java is yet another programming language for AI. It is particularly prevalent in app development, given how many apps utilize AI. It also has libraries and frameworks for AI, including TensorFlow, Deep Java Library, OpenNLP, and so on. Java’s strong typing and performance make it suitable for building large-scale AI systems.


Lisp is among the oldest programming languages still in use and has various beneficial features essential for successful AI projects. Since its beginning, it has been used widely for research purposes in AI problem-solving and natural languages. Today, it is also one of the popular AI languages being used.


C++ is a powerful and efficient programming language often used in AI applications that require high performance, such as computer vision and robotics. C++ is favored for its control over memory and low-level optimization.

These are just a few examples, and other programming languages like Julia, R, and Prolog have been used in AI research and development. The choice of programming language eventually depends on the specific requirements and preferences of the AI project at hand.

The Six Branches of Artificial Intelligence

Artificial intelligence can be broadly categorized into six branches based on the capabilities and functionalities they aim to achieve. The branches of artificial intelligence include:

1. Machine Learning

Machine learning focuses on developing algorithms that allow systems to study the data and improve their performance without being explicitly programmed.

2. Deep Learning

Deep learning is a subgroup of machine learning (ML) that utilizes artificial neural networks with several layers to model and comprehend complex patterns and representations.

3. Natural Language Processing (NLP)

NLP deals with enabling computers to understand, interpret, and generate human language. It involves developing algorithms that can process and analyze text or speech data.

4. Robotics

Robotics combines AI techniques with mechanical engineering and computer science to design and develop intelligent machines that can interact with the physical world.

5. Expert Systems

Expert systems aim to mimic the decision-making capabilities of human experts in specific domains. They use knowledge-based rules and inference engines to provide expert-level advice or solutions.

6. Fuzzy Logic

Fuzzy logic deals with reasoning and decision-making under uncertainty and imprecision by allowing for partial truth values between 0 and 1 rather than solely true or false.

These branches represent different areas of focus within AI, each contributing to specific applications and addressing unique challenges.

The Final Words

In summary, artificial intelligence has become a transformative force, revolutionizing various industries and sectors. We explored the definition of AI, its types, historical background, and programming languages commonly used in AI development.

As AI continues to advance, it holds immense potential to shape the future and drive innovation across numerous domains. So, are you looking forward to integrating AI into your business? Get help from the best software development company right away!