How Artificial Intelligence works?
There Is a misconception in the mind of the people that AI in the era is with robots and self-driving cars. However, the approach leads to failure to recognize AI’s major application in the process, the large amount of data been generated daily.
By analyzing AI to certain processes, gathering data and task automation occurs at a very large scale and unimaginable rate.
Surfing through the waves of data created by humans, AI performs intelligent searches, analyzing and storing both text and images to find related patterns in large and complex data, and then performs action on those learning.
What are the basic components of artificial intelligence?
The major terms of AI’s buzzwords are, “Natural language Processing, Deep Learning & Predictive analytics.” By this data AI enables devices to understand the meaning and reflexes of human language, experience and making predictions, respectively.
Understanding AI major terms or jargons is the way to elaborate discussion about the application in real world in context of this technology. Some basic terms by which humans can understand the interaction of human to technology are:
Machine Learning | Experience Learning
Machine Learning or we say ML, it is the application used by AI to provide device the capability to learn from the day to day usage of the person that helps to improve the experience of the device to react without programming any data to it. ML concentrates on developing algorithms that can predict by analyzing the data. Some examples where AI is used in real life are: prediction of movies or TV shows by Netflix, best route for you Ola or uber ride. It is also being applied in healthcare, life science etc. to accelerate drug development and many more.
Deep Learning | Self-educating machines
Deep learning and machine learning go hand by hand that applies artificial neural networks (ANN) that replies or learns by data that is been processed by the device. ANN mimics the network been used by human brain to learn skills.
A set of ANN performs together to get a unique output from multiple inputs, for example, google lens (searching the image from a mosaic of images). The machine learns from constant processing of data to result the tasks they carry out.
Another example of deep learning is speech recognition, which allows the phone to understand the command like, “Hey Google, Play a song?”
Neural Network | Making associations
Neural networks enable the process of deep learning. The artificial form of a human neuron is known as a perceptron. Just like group of neurons generates a neural network in the brain, bunch of perceptron generates artificial network of neurons in the device.
It learns by processing the examples of training. For instance, the data set of 10000 cat photos. By undergoing the set of images (inputs) the device is able to produce a unique output, solution of the question, “Is the picture the image of cat or not?”
The process analyzes the data multiple times to find links and provide the undefined data the meaning. The whole process defines that the machine has learnt to identify the object successfully and has a positive response.
Cognitive Computing
AI’s another element is Cognitive Computing *which means to imitate and enhance the interaction with humans with machines. Cognitive computing leads to regenerate the thoughts of humans in the device, for instance human language and meaning of pictures.
Both, Artificial intelligence and Cognitive Computing leads to feeding in human like behavior into the device and information processing abilities.
Natural Language Processing (NLP) | Understanding the language
Natural Language Processing (NLP), this permits device to recognize, interpret, and produce human language and speech. The job of natural language processing is to start interaction with machines we utilize in everyday life by understanding the language of humans in context to produce logical responses.
For instance: google translator, which interprets the speech of multiple language in real-time to facilitate communication.
Computer Vision | Understanding images
Computer vision is the technique by which device starts deep learning and identification of pattern to understand the content of the image, it can be in any form (pictures within PDF, tables, graphs as well as other videos and text. It enables device to analyze, process, identify and interpret visual data.
The use of this tech has already been implemented in real life like research & development. It is been used to diagnose patients in a better and faster ways by using computer vision and machine learning to diagnose patients “X-ray scans”.