Artificial Intelligence (AI)
Artificial Intelligence (AI) and Machine Learning are the correlated with each other. These technologies are most trending technologies for creating intelligent systems. Artificial Intelligence and Machine Learning these are two different terms.
Artificial Intelligence (AI) is the ability of a machine to do functions as human do. Robot is one of the best examples of Artificial Intelligence. AI is a program of machine to think and learn just like human being. It is combination of machine and human intelligence. AI is also known as Machine Intelligence which stands for computer system that behaves intelligently. AI is the combination of the word “Artificial” and “Intelligence” which means it creates the intelligent machines with the help of human thinking capability, their behavior. Inshort, AI's goal is to make the systems as smarter as the behavior of the human mind. There are various examples like Learning and planning, speech recognition etc. AI is basically focuses on three things: Learning, Reasoning and Correction. It basically categorized into two parts: Weak AI and Strong AI
Weak AI: Weak AI is generally known as Narrow AI. This kind of AI is designed for specific task. To process the data it uses supervised and unsupervised learning. Apple’s Siri, Industrial Robots, Amazon’s Alexa are some examples of the Weak AI.
Strong AI: Strong AI is also known as Artificial General Intelligence (AGI). It is wider application where the machine has intelligence just like a human. It has the capability of understand the problem, learn and solve it. This application has incredible human intelligence. To process the data is uses clustering and association. Advanced Robotics is the best example of Strong AI.
Artificial Intelligence works on sub domains. Let’s see them one by one:
1. Machine Learning: Now a days, Artificial Intelligence and Machine learning are the trending technologies. These technologies are quite confusing. Machine learning is subset of the AI. ML helps to take decisions based on the past experiences. There are 3 major areas in Machine Learning:
- Supervised Learning: In supervised Learning, the machines are trained by labeled datasets. So that it is easy to classify the data and give the accurate outcome.
For Example: - Object Recognition
- Unsupervised Learning: Unsupervised Learning is harder than the supervised learning. The goal of this is to get the solution of the problem by itself. In this the datasets are not labeled. They are sorted according to the similarities and differences.
- Reinforcement Learning (RL):Reinforcement algorithm is another category of the machine learning algorithm. Reinforcement is the behavior learning model. It is used to teach new tricks to the robot.
For Example: - RL can be used in robotics in industrial automation.
2. Deep Learning: Deep Learning is the type of Machine Learning and AI. When we have number of inputs and outputs the Deep Learning Algorithms are used. As AI is the mimic of the human behavior, the concept of Deep learning is to build the algorithms which mimic the human brain. Self Driving Cars, Automatic Machine Translation are the examples of the Deep Learning.
3. Neural Network: Neural Networks are also known as Artificial Neural Network (ANN). It is also a subset of the machine learning and Heart of the Deep Learning. It contains node layers. Input Layers, Hidden layers and Output Layer.
4. Natural Language Processing: Natural Language Processing (NLP) is another branch of AI. It enables the intelligent machines to understand the human language. Once the machine understands what human wants it responds accordingly. In simple words NLP helps to establish the communication between human and machine. Spell Check, Voice text messaging are some of the examples of NLP.
5. Computer Vision: Computer vision is another field of an AI. It enables the system to understand the images, videos etc. it just act like as a human vision. Computer Vision making the machines visually enabled so that they can understand the image content. The main purpose of computer vision is, without human interference, machine is able to do the work.
Advantages of Artificial Intelligence
- Available 24x7
- Fast Decision Making
- Security Improvement
- Reduction in Human Error
- Efficient Communication
Examples of Artificial Intelligence
- Online Shopping
- Speech Recognition
- Spam Filters on E-mails
- Facial Recognition
- Smart Personal Assistants (Alexa, Siri)
- Fraud Protection and prevention