What is Artificial Intelligence (AI)? Explained

What is Artificial Intelligence (AI)?

Contents:

1. What is Artificial Intelligence (AI)?
2. History of Artificial Intelligence (AI)
3. Types of Artificial Intelligence (AI)
4. How does Artificial Intelligence (AI) Work?
5. Applications of Artificial Intelligence (AI)

What is Artificial Intelligence (AI)?


There is actually a field of science that focuses on making human-like intelligence by using the combination of hardware and software of a machine. These types of machines can learn from experience, adjust to new inputs, and perform human-like tasks. Since they act like humans and made in artificially so they are called Artificial intelligence(AI).

These AI systems are all capable of doing human-like tasks such as they can planning, learning, problem-solving, moving, reasoning, knowledge representation, and, to a lesser extent, social intelligence and creativity.

At first, some algorithms are built on the basis of which they start to work. But over time, they collect information and make decisions by using these different types of information that they have collected.

Since we are at the very beginning of Artificial Intelligence, so it's ok to call it machine learning. Which also is a branch of Artificial Intelligence where machines are taught to learn.

If you are thinking artificial intelligence is only used for space programs and other important purposes then you're thinking wrong. You do not know that you are also surrounded by Artificial Intelligence.

If we talk about Google search, computer games, and virtual assistants such as Amazon's Alexa and Apple's Siri, they are all artificial intelligence, even what you buy online is operated by Artificial Intelligence.

This artificial intelligence can be classified as weak or strong. Weak artificial intelligence, also known as Narrow Artificial Intelligence (NAI). That is an AI system designed and trained for a specific task, such as virtual personal assistants such as Amazon's Alexa and Apple's Siri, a variant of weak AI.

Strong artificial intelligence, also known as Artificial General Intelligence (AGI). That is an AI system with general human cognitive abilities. When presented with a task unfamiliar, a Strong AI system is able to find solutions without human intervention.

These types of artificial intelligence exist only in movies such as The Terminator. They don’t exist in today's reality, but AI experts are sharply divided over whether it will soon become a reality or not.

History of Artificial intelligence


The History of Artificial Intelligence (AI) began in ancient times. But in 1956 the word Artificial Intelligence was first adopted by American computer scientist John McCarthy at the Dartmouth Conference. Read more...

Types of Artificial intelligence


Artificial Intelligence is mainly classified based on two things: One is their capabilities and the other is their functionality. If we talk about their capabilities then there are three types of artificial intelligence Weak Artificial Intelligence, General Artificial Intelligence,  and Super Artificial Intelligence. Read more...

How does Artificial Intelligence (AI) Work?


If we talk about how artificial intelligence works, then first of all some algorithms ( artificial intelligence algorithms ) are built on which they start to work. After that, they start collecting data and improving their performance. If we talk about managing complex business tasks, even managing everything you buy online, depends on the algorithm built in these types of artificial intelligence.

But to understand how Artificial Intelligence actually works, we need to deep dive into the various fields of Artificial Intelligence such as - Machine Learning, Deep Learning, Neural Networks, Natural Language Processing, Computer Vision, and Cognitive Computing, etc.

What is Artificial Intelligence (AI)?


Machine Learning (ML): 

Machine learning (ML) is seen as a sub-domain of artificial intelligence. It is an application of artificial intelligence that enables systems to automatically learn and improve from experience without explicitly programming. It focuses on developing computer programs that can access data and use them to learn for themselves.

The learning process begins with observations or data, such as - direct experience or instruction, to search for patterns of data and to make better decisions in the future based on the examples we provide. The primary goal of machine learning is to allow computers to learn automatically without human intervention.

This is the process that empowers many of the services we use today such as Netflix, YouTube, and Spotify, search engines like Google and Baidu, social-media feeds like Facebook and Twitter, voice assistants like Siri and Alexa, etc.

Deep Learning (DL):

Deep Learning (DL) is seen as a sub-domain of Machine learning (ML). Deep Learning concerned with algorithms called Artificial Neural Networks (ANNs), which were inspired by information processing and distributed communication nodes in biological brain systems.

But there are many differences between the biological brain and these ANNs. For example, ANNs tend to be static and symbolic, where the biological brain tends to be most living organisms which are dynamic and analog.

Deep learning algorithms are often categorized as supervised, unsupervised, and reinforcement. If we talk about supervised learning,  then it is labeled to tell the machine exactly what patterns it should look for. But In unsupervised learning, the data has no labels. Here the machine just looks for whatever patterns it can find. A reinforcement machine learning algorithm is a learning method that creates actions by interacting with its environment and discovering errors or rewards.

Deep learning has some architectures such as deep neural networks, recurrent neural networks and convolutional neural networks which have been applied to various fields of technology such as computer vision, machine vision, speech recognition, audio recognition, natural language processing, social network filtering, medical image analysis, and material inspection, etc.

Neural Networks:

Neural Network is a circuit of neurons consisting of artificial neurons or nodes and operate on the same principles as human neural cells operate. In these artificial neurons, there are a series of algorithms that process data between different underlying variables and processes the data as a human brain does.

Natural Language Processing (NLP):

Natural Language Processing (NLP) is a sub-domain of artificial intelligence. It is a science of speech recognition, reading, understanding, and interpreting a language by a device or machine. Once the machine understands how users intend to communicate, it responds accordingly to it.

Computer Vision:

Computer Vision is a field of artificial intelligence which concerned with the theory and technology for building artificial systems that obtain information from images, videos, or multi-dimensional data.

This algorithm is used to understand an image by breaking down, studying different parts of the objects, and make a better output decision based on previous observations. In this process, computers can gain a high-level understanding of digital images or videos.

Cognitive Computing:

Cognitive Computing algorithms animate text, speech, images, objects in a way that mimics a human brain and tries to give a  person his desired output.

Using these above methods the works of artificial intelligence are performed.

Applications of Artificial Intelligence (AI)


Artificial Intelligence (AI) enhances the efficiency of doing any task that is why it is used in various fields of industries, including finance, healthcare, education, transportation, etc.

1. Artificial Intelligence in Healthcare:

Artificial intelligence is helping physicians. Many companies are applying artificial intelligence to diagnose better and faster than humans. One of the most well-known technologies is IBM's Watson which understands natural language and can answer questions about it.

Using a technology called Bloomberg, Microsoft has developed an AI system that helps doctors to find the right treatments for cancer. In so many ways, artificial intelligence is helping in healthcare today.

2. Artificial Intelligence in business:

Robotic automation process, machine learning algorithms are being integrated into Customer Relationship Management (CRM) platforms to uncover information on how to better serve customers. Artificial intelligence has already been incorporated into e-commerce sites to provide immediate service to customers.

3. Artificial Intelligence in Autonomous vehicles:

Like humans, self-driving vehicles need to have sensors to understand the world around them and a brain to collect, process, and select specific actions based on the information collected. Autonomous vehicles are equipped with advanced equipment for data collection, including long-range radar, cameras, and leaders.

Each of the technologies is used in an individual capacity and each collects individual information. This information is useless unless it is processed and some form of information is taken based on the information gathered. This is where artificial intelligence works and it can be compared to the human brain.

4. Artificial Intelligence in education:

This automates grading, giving educators/instructors more time. It helps students evaluate and work at their own pace, adapting to their needs. Artificial intelligence is also used in various fields of Agriculture, Military, Cybersecurity, and Arts, etc.



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