Application of Machine Learning in Artificial Intelligence
From early ages, the human had started to reconstruct the world into a digital form. As a result of that, they could invent different machines and the computer. Now we are in a modernized world and current era we called Information era or technological era. Human life without technology has become pointless in today’s dynamic world and technology is updating day by day. There are a vast number of emerging technologies were identified that would change the future world more. Some examples are AI, Robotics, Nanotechnology, Cloud Computing, IoT, Blockchain, Natural Language Processing, Quantum Computing, etc. Artificial Intelligence is recognized as one of the greatest and very popular upcoming technology trends for years.
What is AI?
AI is referred to as Artificial Intelligence and it is the technology that aims to simulate human intelligence in a machine or a program. Those machines or programs learn to perform tasks usually performed by humans that require a kind of human intelligence. It contains the abilities of the human brain such as learning, planning, reasoning, decision making, and problem-solving. Narrow AI, General Ai, Super AI, Reactive machines, Self-awareness, and Theory of Mind are some types of AI. The applications of Artificial Intelligence are helpful to achieve the respected targets in AI. Those Applications are, Machine Learning, Neural Networks, Expert Systems, Fuzzy Logic, etc.
What is Machine Learning?
Machine Learning is an application of AI which provides the ability to learn from the data and automatically improve itself from experience without being explicitly programmed. It focuses on enabling algorithms to learn from data provided, gather insights and make predictions on previously unanalyzed data using gathered information. Supervised learning, Unsupervised Learning, and Reinforcement learning are the main approaches to Machine Learning.
Machine learning is growing faster day by day. We use ML applications in our day-to-day lives without even knowing about them such as Virtual Personal Assistants, traffic predictions, filtering of malware and spam emails, chatbots, online fraud detection, etc. Almost every field is using ML to achieve its eminently worthwhile goals. Let’s see some trending real-world applications of machine learning.
Image recognition is the very most common application of ML. It is called the ability of a computer-powered camera to identify and detect people, places, objects, and features in a digital image or video. This kind of algorithm includes Optical character recognition, Pattern matching, and gradient matching, face recognition, license plate matching, and scene identification. One of the best and popular examples that can be given is the automatic tagging suggestions feature provided by Facebook and for that face detection and recognition, the algorithm is being used. Google Lens is another interesting application that uses deep machine learning not only to detect objects but also offer features like scanning, translation, shopping, places, and more. In automatic language-translation uses Neural Machine Learning that translates the text into a language the user is being familiar with.
Virtual private assistants and speech recognition are the two most popular applications in machine learning. Speech recognition is the process that converts the human voice into a form of text. Virtual assistants like Google Assistant, Siri, Alexa use this technology and it’s done by recording human voice, and then it is sent over the server on a cloud and it is decoding using machine learning algorithms and perform the specific task that is asked by the user. They help humans in various ways just by using human voice instructions such as calling someone in the contact list, playing music, scheduling appointments, and even the user can ask for a joke when they are bored. In 2020, Google has announced that the google assistant is being used by 500 Million users all over the world.
Traffic Prediction is one of the most useful facilities in today’s busy world. Google Maps is capable of showing the correct and the shortest route and predicting the traffic conditions to arrive at a specific destination of the user. It uses both the real-time location of the vehicle and the historical traffic patterns to predict the traffic conditions such as whether traffic is light or heavy.
By using the unsupervised learning method in Machine learning, Tesla one of the most popular car manufacturing company were working on creating a self-driving car. Continuous rendering of the surrounding environment and the prediction of possible changes to those surroundings are the main tasks of a machine learning algorithm in a self-driving car. These are achieved via object detection, object identification or recognition object classification, object localization, and prediction of movement like sub-tasks. This invention is a turning point in the Car industry.
We receive a considerable number of emails per day. They all are automatically filtered as important, promotion, and spam likewise in different folders. Machine learning is the technology behind this spam email and malware filtering. Header, Content, permission, general blacklists, and rules-based are some types of filters used in Gmail. And some machine learning algorithms used for spam email filtering and malware detection are Decision trees, Naïve Bayes classifier, and Multi-Layer Perception. This feature provides some protection against harmful computer viruses, saves time, and some more advantages.
The above-mentioned applications are all used in day-to-day activities. Not only in day-to-day activities but also in other major industries like, health sector, sports, politics and government, transport, gaming, and more ML is used very effectively. Astronomy, one of the oldest sciences and a fast-growing industry today uses AI for almost all projects. A deep-learning framework which is a sub-set of Machine learning was developed to perform pixel-level morphological classifications of objects in astronomical images and it is called the Morpheus project. A navigation system that helps to navigate the surface of planets through the shortest possible routes was also developed by using this technology.
As a subset of AI, Machine learning is playing an important role in today’s world. It has become a technology humans can’t live without as it is making human lives and their works easy day by day.
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