AI stands for artificial intelligence. AI can be described as a computer system performing certain tasks which involve human intelligence or something similar to it. AI has been accepted worldwide and is growing with time.
In machines, we perform simulations of human intelligence, and machines are programmed to learn and imitate human actions. With experience and time machine learns to perform tasks like a human.
Such technologies contribute a lot to improving the quality of our lives. Every one of us wants to get connected with AI technology somehow not necessary that people pursuing their career in AI only need it.
How do AI works?
Artificial intelligence works by collecting huge data and performing repetitive processes and intelligent algorithms that allow the software to learn on its own with the help of patterns available in the data.
Building an AI system is an extremely delicate process that involves reverse engineering of human nature, capabilities, and more in a computer.
For understanding the working of an AI-based computer system first you need to understand different sub-domains of AI and how these domains are applicable in diversified fields.
1. Machine Learning
It tells a machine how to make decisions based on previous experiences. The machine identifies patterns, performs a thorough analysis of the past data available to determine the meaning of these patterns, and concludes a possible outcome. With the help of methods from physics, operation research and statistics machine learn insights of the data. The machine concludes automatically without any human interference and ultimately saves a lot of human time.
2. A Neural Network
Neural networks work similarly to the nerve cells of a human being. In this process data is analyzed through multiple passes and a connection is found in undefined data and its meaning is learned. Using multiple algorithms a relationship is built between various underlying variables and further data is processed as the human brain processes it.
3. Deep Learning
It tells a machine how to process a specific input via multiple layers and classify and predict the viable outcome. It makes use of massive neural networks and makes use of improvised training methods to understand the complex pattern of huge data. Speech recognition and image are common applications. The processing of data is done similar to what the human brain does.
4. Computer Vision
It is dependable on pattern interception and deep learning to understand what is there in a specific video or image. What it does is break down a picture and study its different parts separately. When a computer system process, research and learn images, they proceed to capture images or videos in real-time and further interpret its surroundings.
5. Natural Language Processing (NLP)
It is the capability to research, learn and generate a language of human beings including speech. The further stage of NLP includes learning natural language interaction, it allows a person to interact with the machine using regular language and get the task done. Once a computer learns what a person is trying to say it gives the response accordingly.
