Artificial Intelligence

Artificial Intelligence

The science of building smart machines capable of performing tasks that makes it possible for machines to learn from experience, adjust to new inputs, and perform human-like tasks.  Learn about implications for our future its applications

Introduction

The technique called “deep learning”, has achieved astonishing results in several domains, most notably in understanding natural language in the past few years. Research teams use it to teach computers to find meaning in vast amounts of text. Artificial intelligence (AI) is the intelligence exhibited by machines or software, and the branch of computer science that develops machines and software with human-like intelligence. Major AI researchers and textbooks define the field as "the study and design of intelligent agents", where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.

John McCarthy, who coined the term in 1955, defines it as "the science and engineering of making intelligent machines".

Application of Technology

The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception, and the ability to move and manipulate objects. Currently, popular approaches include deep learning, statistical methods, computational intelligence, and traditional symbolic AI. There is an enormous number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others.

The ability of machines to exhibit advanced cognitive skills to process natural language, to learn, to plan or to perceive, makes it possible for new tasks to be performed by intelligent systems, sometimes with more success than humans. By using AI-driven automation in existing industries, alongside using AI technologies in new emerging areas, artificial intelligence could vastly boost productivity and economic growth.

AI is also a technology that comes with challenges, such as accountability, security, technological mistrust, and the displacement of human workers.

Business Case Example

  1. Self-Driving Cars: In the future, AI will shorten your commute using self-driving cars that result in fewer accidents, more efficient ride-sharing, and smart traffic lights that reduce wait times resulting in reducing the overall travel time.
  2. Smart Email Categorization: Gmail uses AI to categorize your emails into primary, social, and promotion inboxes, as well as labeling emails as important. Every time you mark an email as important, Gmail learns. The researchers tested the effectiveness of Priority Inbox on Google employees and found that those with Priority Inbox “spent 6% less time reading email overall.
  3. Mobile Check Deposits: Most large banks offer the ability to deposit checks through a smartphone app, eliminating a need for customers to physically deliver a check to the bank. According to a 2014 SEC filing, the vast majority of major banks rely on technology developed by Mitek, which uses AI and ML to decipher and convert handwriting on checks into text via OCR.  

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