{"id":598,"date":"2020-02-25T14:16:12","date_gmt":"2020-02-25T14:16:12","guid":{"rendered":"https:\/\/www.aeologic.com\/blog\/?p=598"},"modified":"2022-12-15T10:45:34","modified_gmt":"2022-12-15T10:45:34","slug":"what-is-the-difference-between-artificial-intelligence-and-machine-learning","status":"publish","type":"post","link":"https:\/\/www.aeologic.com\/blog\/what-is-the-difference-between-artificial-intelligence-and-machine-learning\/","title":{"rendered":"What Is The Difference Between Artificial Intelligence And Machine Learning?"},"content":{"rendered":"<p>Artificial Intelligence, Machine Learning, Augmented Reality or Merged Reality, these are 4 different terms that are used interchangeably but don\u2019t quite refer to the same inference. Knowing this difference is quite significant since several marketing agencies often overlook the distinction that can later affect advertising and sales.<\/p>\n<h2>Difference<strong> Between Artificial Intelligence And Machine Learning<\/strong><\/h2>\n<p><a href=\"https:\/\/www.aeologic.com\/blog\/what-is-the-difference-between-artificial-intelligence-and-machine-learning\/\"><strong>Artificial Intelligence And Machine Learning <\/strong><\/a>do have a great deal of overlap, but they are not interchangeable. So to clear the confusion in basic terms- <strong><em>Machine Learning produces predictions and Artificial Intelligence produces actions. <\/em><\/strong>Although this simplified statement isn\u2019t a sufficient qualification it is a heads-up for the detailed differentiation that follows-<\/p>\n<p><strong>Machine Learning produces predictions-<\/strong> Machine Learning is basically a language in which the machine can educate itself without being pre-programmed. It is an application used for implementing Artificial Intelligence, where it provides the system with an ability to automatically learn from its actions and then improvise from experience.<\/p>\n<p><em>\u201cMuch of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type \u2014 quietly but meaningfully improving core operations.\u201d <\/em>&#8211; Jeff Bezos<\/p>\n<h2>Machine Learning is a Subfield of Artificial Intelligence<\/h2>\n<p><strong>Artificial Intelligence produces actions- <\/strong>Artificial Intelligence is the most recognized of the other three designations but is the most challenging to define. Here are are few areas, where AI is used at present-<\/p>\n<ul>\n<li>Control Theory and Robotics<\/li>\n<li>Game-playing algorithms<\/li>\n<li>Natural Language Processing<\/li>\n<li>Reinforcement Learning<\/li>\n<li>Optimization (Google Maps)<\/li>\n<\/ul>\n<p><em>\u201cArtificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.\u201d- Ray Kurzweil<\/em><\/p>\n<p>AI can be translated as fusing human intelligence in machines. There are basically two kinds of AI machines- General and Narrow. General AI machines can easily solve problems whereas Narrow AI machines can only perform specific tasks, better than humans but with only a limited scope.<\/p>\n<p>The aim of Artificial Intelligence is to learn by acquiring knowledge and progress whilst applying that knowledge.<\/p>\n<h3>\u00a0The Systematic Difference Between Artificial Intelligence and Machine Learning<\/h3>\n<table width=\"624\">\n<tbody>\n<tr>\n<td style=\"text-align: center;\" width=\"312\"><strong>Artificial Intelligence<\/strong><\/td>\n<td style=\"text-align: center;\" width=\"312\"><strong>Machine Learning <\/strong><\/td>\n<\/tr>\n<tr>\n<td width=\"312\">Ambition is to increase the rate of success and not accuracy<\/td>\n<td width=\"312\">Ambition is to increase the accuracy rate<\/td>\n<\/tr>\n<tr>\n<td width=\"312\">It mimics natural intelligence to solve complex problems<\/td>\n<td width=\"312\">It learns from the data in order to maximize machine performance<\/td>\n<\/tr>\n<tr>\n<td width=\"312\">Decision making<\/td>\n<td width=\"312\">The main idea is to learn from the data withdrawn from tasks performed<\/td>\n<\/tr>\n<tr>\n<td width=\"312\">AI will find the optimal solution<\/td>\n<td width=\"312\">The goal is to only find the solution where optimal might not be a priority<\/td>\n<\/tr>\n<tr>\n<td width=\"312\">Leads to wisdom and intelligence<\/td>\n<td width=\"312\">Leads to knowledge<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3><strong>\u00a0<\/strong><strong>Artificial Intelligence and Machine Learning &#8211; The Difference Through an Example <\/strong><\/h3>\n<p>If we have to build a self-driving car, and the problem to be worked upon is- stopping at signals, then skills have to be withdrawn from Artificial Intelligence, and Machine Learning and Deep Learning.<\/p>\n<p><em>What will AI do?<\/em> The car has to decide when to apply brakes and at what signals? Here AI comes into the picture as it uses control theory to recognize signals, roadblocks, and slippery roads.<\/p>\n<p><em>What will ML do?<\/em> After embedding several images of roadblocks, signals, and corrupt roads in the database, and the algorithm will have to be designed in order to ensure predictions.<\/p>\n<p>Further, to implement and fabricate these two into the automobile\u2019s mind, deep learning or data science is required. Similarly, AI has mastered automated consumer interactions, by utilizing the smart combinations of policy graph algorithms and Machine Learning.<\/p>\n<h3><strong>Final Words<\/strong><\/h3>\n<p>Both Artificial Intelligence and Machine Learning are a product of human intelligence. The applications, utility and implementation of both the skills can be done either dangerously or rightfully to encourage economic growth. <a href=\"https:\/\/www.aeologic.com\/\"><strong>AeoLogic<\/strong><\/a> works with the Government of India and NIC as a consultant in order to speed up the AI outcomes. Get in touch for enterprise consultation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial Intelligence, Machine Learning, Augmented Reality or Merged Reality, these are 4 different terms that are used interchangeably but don\u2019t quite refer to the same inference. Knowing this difference is quite significant since several marketing agencies often overlook the distinction that can later affect advertising and sales. Difference Between Artificial Intelligence And Machine Learning Artificial Intelligence And Machine Learning do have a great deal of overlap, but they are not interchangeable. So to clear the confusion in basic terms- Machine Learning produces predictions and Artificial Intelligence produces actions. Although this simplified statement isn\u2019t a sufficient qualification it is a heads-up for the detailed differentiation that follows- Machine Learning produces predictions- Machine Learning is basically a language in which the machine can educate itself without being pre-programmed. It is an application used for implementing Artificial Intelligence, where it provides the system with an ability to automatically learn from its actions and then improvise from experience. \u201cMuch of what we do with machine learning happens beneath the surface. Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type \u2014 quietly but meaningfully improving core operations.\u201d &#8211; Jeff Bezos Machine Learning is a Subfield of Artificial Intelligence Artificial Intelligence produces actions- Artificial Intelligence is the most recognized of the other three designations but is the most challenging to define. Here are are few areas, where AI is used at present- Control Theory and Robotics Game-playing algorithms Natural Language Processing Reinforcement Learning Optimization (Google Maps) \u201cArtificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.\u201d- Ray Kurzweil AI can be translated as fusing human intelligence in machines. There are basically two kinds of AI machines- General and Narrow. General AI machines can easily solve problems whereas Narrow AI machines can only perform specific tasks, better than humans but with only a limited scope. The aim of Artificial Intelligence is to learn by acquiring knowledge and progress whilst applying that knowledge. \u00a0The Systematic Difference Between Artificial Intelligence and Machine Learning Artificial Intelligence Machine Learning Ambition is to increase the rate of success and not accuracy Ambition is to increase the accuracy rate It mimics natural intelligence to solve complex problems It learns from the data in order to maximize machine performance Decision making The main idea is to learn from the data withdrawn from tasks performed AI will find the optimal solution The goal is to only find the solution where optimal might not be a priority Leads to wisdom and intelligence Leads to knowledge \u00a0Artificial Intelligence and Machine Learning &#8211; The Difference Through an Example If we have to build a self-driving car, and the problem to be worked upon is- stopping at signals, then skills have to be withdrawn from Artificial Intelligence, and Machine Learning and Deep Learning. What will AI do? The car has to decide when to apply brakes and at what signals? Here AI comes into the picture as it uses control theory to recognize signals, roadblocks, and slippery roads. What will ML do? After embedding several images of roadblocks, signals, and corrupt roads in the database, and the algorithm will have to be designed in order to ensure predictions. Further, to implement and fabricate these two into the automobile\u2019s mind, deep learning or data science is required. Similarly, AI has mastered automated consumer interactions, by utilizing the smart combinations of policy graph algorithms and Machine Learning. Final Words Both Artificial Intelligence and Machine Learning are a product of human intelligence. The applications, utility and implementation of both the skills can be done either dangerously or rightfully to encourage economic growth. AeoLogic works with the Government of India and NIC as a consultant in order to speed up the AI outcomes. Get in touch for enterprise consultation.<\/p>\n","protected":false},"author":3,"featured_media":600,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[68,90],"tags":[],"class_list":["post-598","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-machine-learning"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Difference Between Artificial Intelligence And Machine Learning<\/title>\n<meta name=\"description\" content=\"Discuss the difference between artificial intelligence and machine learning. 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