Artificial Intelligence is a technology of computer science that enables the creation of intelligent machines that behave, work and react like humans. Artificial Intelligence has become a very essential part of the technology industry. Researches associated with artificial intelligence are highly technical and specialized.
Applications of AI include expert systems, speech recognition, machine vision and many more. Artificial Intelligence can be categorized into weak AI and Strong AI. Weak AI is an AI system that is designed and trained only for a particular task. Examples include virtual personal assistants, such as Apple’s Siri. Strong AI is an AI system which can find a solution without human intervention even in unfamiliar tasks.
Machine Learning is a part of Artificial Intelligence that enables systems to automatically learn and improve from experience on their own without being explicitly programmed. It gives computers “The ability to learn” which makes them more similar to humans. This is achieved by developing computer programs that can access data and system to train themselves from that data to learn.
There are a number of services offered by Artificial Intelligence which has transformed the world of technology. We will be discussing some of them.
Services offered by Artificial Intelligence
Human and computer vision :
In human vision, the eyes act as image receptors that capture light and convert it into the signals which are then transmitted to image processing centers in the brain. These centers start processing the signals received from the eyes and build an internal “picture” of the scene being viewed.
Computer vision is a technology that concerns with how the computer visually perceives the world around it. As we know, Computers are great at doing huge tasks like finding tenth-root of a 1000 digit number but struggle in simple tasks of recognizing and differentiating various objects. Recent advances in Deep Learning and availability of the labeled datasets (possible with Artificial Intelligence) with high computing power have made it possible for CV systems to outperform their human counterparts for some narrowly defined tasks like visual object classification.
Video object tracking :
Object detection, a branch of Computer Vision, visually observes objects that are in images of different videos and detects them with the help of computers. If we talk about image, it is a single frame that captures a single-static instance of a naturally occurring event. Now, if we talk about video, it contains many instances of static images displayed in one second, inducing the effect of viewing a naturally occurring event.
A single static image in a video is what we call a video frame. In most videos, the number of frames encountered in one second of the video ranges between 20 to 32, and this value is known as frames-per-second (fps).
Detecting objects in images and videos was not possible earlier but now, detecting them accurately has become highly successful due to the rise of machine learning and deep learning algorithms, all of which come under Artificial Intelligence. New algorithms have been developed that detects, locates, and recognizes objects in images and videos, some of which include RCNNs, SSD, RetinaNet, YOLO, and others.
Detection of objects in images and videos is a highly technical and time-consuming process, it requires an understanding of applied mathematics and solid technical knowledge of the algorithms as well as thousands of lines of code.
Speech and audio Recognition :
Speech recognition is an Artificial Intelligence technology that recognizes spoken words, which can then be converted to text. A subset of speech recognition is voice recognition, which identifies a person based on their voice.
Examples include Facebook, Amazon, Webtunix, Microsoft, Google, and Apple, which are five of the world’s top tech companies and are offering this feature on various devices through services like Google Home, Amazon Echo, and Siri. All this has become possible only with the Artificial Intelligence technology.
Reinforcement Learning :
Reinforcement Learning is a sub-part of Artificial Intelligence and can be defined as the closed-form of learning to the way in which a human being learns. It contains an intelligent agent that interacts with its environment smartly and results in a numerical reward. The goal of the agent is learning sequential actions so as to maximize a long time reward. Just like a human being who learns from his experiences with the real world, keep exploring new things and updating his values and beliefs, the Reinforcement Learning agents work in the similar way to maximize his own rewards in the long run.
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Natural Language Processing :
Natural Language Processing (NLP) systems are those that are able to perceive and understand the spoken human language. It consists of various subtasks like speech recognition, natural language understanding, generation, and translation. Multiple languages are used across the globe, and NLP systems could play the role of a real changer. Recent NLP research includes developing chatbots that can dynamically interact with humans. Any query asked by humans will be answered through computers with the help of chatbots.
NATURAL LEARNING PROCESS
Recommender Systems :
Another sub-technology of Artificial Intelligence is Recommender systems that are present everywhere in today’s digital world. Examples include online shopping sites where options are displayed according to your previous shopping decisions.
From what to read, what to buy, to whom to date, Recommender Systems are present everywhere and have taken the place of the salesman in the virtual world. The annoying behavior of salesman to insist on buying products has been replaced by the Recommender systems where options are displayed according to the user’s interest. Companies like Netflix and Amazon rely on RS. It takes into consideration a user’s past preferences, and trends to make an effective recommendation. Artificial Intelligence is becoming popular in healthcare and predict the symptoms of diseases and recommend the doctor based on results.
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Planning in AI is about the decision making tasks performed by the robots or the computer programs to achieve a particular goal. The execution of planning takes place in such a way that the sequence of actions is performed with a high likelihood to complete the specific task.
Planning acts as a key ability for intelligent systems, increasing their autonomy and flexibility through the construction of sequences of actions to achieve their goals. Technologies like robotics, process planning, web-based information gathering, autonomous agents and spacecraft mission control, all work according to planning.
Robotics is a separate branch of its own but it does have some overlapping with AI. Robot navigation in the dynamic environment has been made possible with the help of AI. If we take the example of the self-driving car, then how do you make sure that a self-driving car goes from point A to point B without harming itself and anyone else in the least time? Advances in Deep Learning and Recommender systems have made it possible.
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