Global Artificial Intelligence for Enterprise Applications 2016-2025: 31.2 Billion Market Analysis and Forecasts - 200 Use Cases for AI That are Classified Into 25 Industry Sectors - Research and Markets

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The analysis has identified nearly 200 real-world enterprise use cases for AI that are classified into 25 industry sectors. The firm forecasts that revenue for enterprise AI applications will increase from 358 million in 2016 to 31.2 billion by 2025, representing a compound annual growth rate (CAGR) of 64.3%. Artificial intelligence (AI) technologies are quickly gaining mindshare among corporate executives around the world, driving a proliferation of use cases that touch virtually every industry. AI technologies, which include deep learning, machine learning, natural language processing (NLP), and computer vision, among others, are designed to endow computers with human-like faculties such as hearing, seeing, reasoning, and learning. But AI enables computers to do some things better than humans, especially when it comes to processing very large amounts of data quickly, efficiently, and accurately.


Global Artificial Intelligence Market Analysis & Trends 2013-2016 - Industry Forecast to 2025 - Research and Markets

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DUBLIN--(BUSINESS WIRE)--Research and Markets has announced the addition of the "Global Artificial Intelligence Market Analysis & Trends - Industry Forecast to 2025" report to their offering. The Global Artificial Intelligence Market is poised to grow at a CAGR of around 44.3% over the next decade to reach approximately 23.4 billion by 2025. This industry report analyzes the global markets for Artificial Intelligence across all the given segments on global as well as regional levels presented in the research scope. It presents historical market data for 2013, 2014 revenue estimations are presented for 2015 and forecasts from 2016 till 2025. The study focuses on market trends, leading players, supply chain trends, technological innovations, key developments, and future strategies.


Artificial Intelligence for Enterprise Applications: Global Market Analysis and Forecasts

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Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Machine Reasoning, and Strong AI Artificial intelligence (AI) technologies are quickly gaining mindshare among corporate executives around the world, driving a proliferation of use cases that touch virtually every industry. AI technologies, which include deep learning, machine learning, natural language processing (NLP), and computer vision, among others, are designed to endow computers with human-like faculties such as hearing, seeing, reasoning, and learning. But AI enables computers to do some things better than humans, especially when it comes to processing very large amounts of data quickly, efficiently, and accurately. Investment is flowing rapidly into the development of AI technologies, both at the startup level as well as within some of the world's leading technology companies. Meanwhile, innovation in AI algorithms is progressing at a breakneck pace and industry players are scrambling to determine the optimal platforms to deliver AI-enabled services on a cost-effective basis across an ever-expanding set of use cases.


Stock Market Analysis: Machine Learning and the Indian Auto Sector

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The efficient stock market hypotheses (EMH) has been the subject of much controversy and research since its publication. The EMH is an investment theory that asserts that it is impossible to out perform market returns. According to the hypothesis, it is not possible because of stock market efficiency. Stock market efficiency causes share prices to incorporate and reflect all pertinent market information. By the nature of this assertion it makes it impossible for the stock to be either over or undervalued.


Machine Learning and Artificial Intelligence in Marketing Research

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Machine learning, artificial intelligence, deep learning… Unless you've been living under a rock, chances are you've heard these terms before. Indeed, they seem to have become a must for market researchers. Unfortunately, so many precise terms have never meant so little! For computer scientists these terms entail highly technical algorithms and mathematical frameworks; to the layman they are synonyms; but as far as most of us should be concerned, increasingly, they are meaningless. My engineers would severely chastise me if I used these words incorrectly--an easy mistake to make since there is technically no correct or incorrect way to use these terms, only strict and less strict definitions.