What is Artificial Intelligence? Understand artificial intelligence in 5 minutes
Read this article to understand the significant impact of Artificial Intelligence in our day to day lives.
- What is Artificial Intelligence?
- Subfields of Artificial Intelligence
- How Artificial Intelligence Development works and how is it related to Human Brain
- Here are some of the learning algorithms used to make machines Artificially Intelligent
What is Artificial Intelligence?
Artificial Intelligence (AI) is a broad branch of computer science, aiming to create systems that can function intelligently and independently just like humans.
AI is an imitation of human intelligence processes by machines. The intelligence processes include learning, reasoning, and self-correction. Specific AI applications include machine vision, speech recognition, and expert systems.
After understanding what is artificial intelligence, you need to know how it works and what are the components that make machines work intelligently.
Subfields of Artificial Intelligence
Humans can speak and listen to communicate through language; this is the field of speech recognition. Since speech recognition is statistically based, hence it’s called statistical learning.
Natural Language Processing
Humans can write and read the text in a language; this is the field of NLP or natural language processing.
Humans can see with their eyes and process what they see; this is the field of computer vision. Computer vision falls under the symbolic way for computers to process information.
Moreover, they can recognize the surroundings around them through their eyes which create images of that world. This field of image processing which even though is not directly related to AI is required for computer vision.
Humans can understand their environment and move around fluidly; this is the field of robotics. Robotic Process Automation improves efficiency of business’s productivity and processes by automating repetitive and complex tasks.
Humans can see patterns such as grouping of like objects; this is the field of pattern recognition. Machines are even better at pattern recognition because they can use more data and dimensions of data, this is the field of machine learning.
Now let’s talk about the human brain, the human brain is a network of neurons, and we use neurons to learn things.
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How Artificial Intelligence Development works and how is it related to Human Brain
Understanding what is artificial intelligence is is not enough until you know how it comes into play. Read further to know how artificial intelligence works.
If we can replicate the structure and the function of the human brain, we might be able to get cognitive capabilities in machines; this is the field of neural networks.
If these networks are more complex and more in-depth and we use those to learn complicated thing that is the field of deep learning.
There are different types of deep learning and machines that are fundamentally different techniques to replicate what the human brain does.
If we get the network to scan images from left to right top to bottom, it’s a convolution neural network. But what is CNN?
A CNN is used to recognize objects in a scene; this is how computer vision fits in object recognition is accomplished through AI.
Humans can remember the past as what you had for dinner last night, well at least most of us. We can get a neural network to recognize a limited past this is a recurrent neural network.
As you see there are two ways an eye works, one is symbolic-based, and another is data-based. For the database side, it is called machine learning as we need to feed the machine lots of data before it can learn.
For example, if you had lots of data for sales versus advertising spend you can plot that data to see some pattern. If the machine can learn this pattern, then it can make predictions based on what it has learned.
While one or two or even three dimensions are natural for humans to understand and learn, machines can learn in many more aspects like even a hundred or thousands. That’s why devices can look at lots of high-dimensional data and determine patterns.
Once it learns these patterns, it can make predictions that humans cannot even come close to. We can use all these machine learning techniques to do one of two things, classification or prediction.
As an example, when you use some information about customers to assign new customers to a group like young adults, then you are classifying their customer.
If you use data to predict if they’re likely to defect to a competitor, then you’re making a prediction.
There are certain learning algorithms that are used in the AI development process to run the machines smartly. Let’s understand how different learning algorithms perform.
Here are some of the learning algorithms used to make machines Artificially Intelligent
- Supervised Learning
If you train an algorithm with data, which also contains the answer, then it’s called supervised learning. For example when you train a machine to recognize your friends by name you’ll need to identify them for the computer.
- Unsupervised Learning
If you train an algorithm with data where you want the machine to figure out the patterns, then it’s unsupervised learning. For example, you might want to feed the data about celestial objects in the universe and expect the machine to come up with patterns in that data by itself.
- Reinforcement Learning
If you give any algorithm a goal and expect the Machine through trial-and-error to achieve that goal, then it’s called reinforcement learning. A robot’s attempt to climb over the wall until it succeeds is an example of that.
AI Development has the potential to reconstruct businesses with its innovative features like natural language processing, machine learning, image processing, and robotic process automation.
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